forked from mindspore-Ecosystem/mindspore
Add full support for cpu cast op
This commit is contained in:
yanglf1121
parent
24792571b1
commit
8987b3dbd1
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@ -73,40 +73,162 @@ bool CastCPUKernel::Launch(const std::vector<kernel::AddressPtr> &inputs,
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using TypePair =
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std::function<void(const std::vector<kernel::AddressPtr> &, const std::vector<kernel::AddressPtr> &)>;
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std::map<TypeId, std::map<TypeId, TypePair>> mode_map;
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mode_map[kNumberTypeFloat32][kNumberTypeFloat32] = LaunchCast<float, float>;
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mode_map[kNumberTypeFloat32][kNumberTypeInt32] = LaunchCast<float, int>;
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mode_map[kNumberTypeFloat32][kNumberTypeBool] = LaunchCast<float, bool>;
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mode_map[kNumberTypeInt32][kNumberTypeFloat32] = LaunchCast<int, float>;
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mode_map[kNumberTypeInt32][kNumberTypeInt32] = LaunchCast<int, int>;
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mode_map[kNumberTypeInt32][kNumberTypeBool] = LaunchCast<int, bool>;
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mode_map[kNumberTypeBool][kNumberTypeFloat16] = LaunchCast<bool, float16>;
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mode_map[kNumberTypeBool][kNumberTypeFloat32] = LaunchCast<bool, float>;
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mode_map[kNumberTypeBool][kNumberTypeFloat64] = LaunchCast<bool, double>;
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mode_map[kNumberTypeBool][kNumberTypeInt8] = LaunchCast<bool, int8_t>;
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mode_map[kNumberTypeBool][kNumberTypeInt16] = LaunchCast<bool, int16_t>;
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mode_map[kNumberTypeBool][kNumberTypeInt32] = LaunchCast<bool, int32_t>;
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mode_map[kNumberTypeBool][kNumberTypeInt64] = LaunchCast<bool, int64_t>;
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mode_map[kNumberTypeBool][kNumberTypeUInt8] = LaunchCast<bool, uint8_t>;
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mode_map[kNumberTypeBool][kNumberTypeUInt16] = LaunchCast<bool, uint16_t>;
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mode_map[kNumberTypeBool][kNumberTypeUInt32] = LaunchCast<bool, uint32_t>;
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mode_map[kNumberTypeBool][kNumberTypeUInt64] = LaunchCast<bool, uint64_t>;
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mode_map[kNumberTypeBool][kNumberTypeBool] = LaunchCast<bool, bool>;
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mode_map[kNumberTypeBool][kNumberTypeInt32] = LaunchCast<bool, int>;
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mode_map[kNumberTypeFloat16][kNumberTypeFloat16] = LaunchCast<float16, float16>;
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mode_map[kNumberTypeFloat16][kNumberTypeFloat32] = LaunchCast<float16, float>;
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mode_map[kNumberTypeFloat16][kNumberTypeFloat64] = LaunchCast<float16, double>;
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mode_map[kNumberTypeFloat16][kNumberTypeInt8] = LaunchCast<float16, int8_t>;
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mode_map[kNumberTypeFloat16][kNumberTypeInt16] = LaunchCast<float16, int16_t>;
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mode_map[kNumberTypeFloat16][kNumberTypeInt32] = LaunchCast<float16, int32_t>;
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mode_map[kNumberTypeFloat16][kNumberTypeInt64] = LaunchCast<float16, int64_t>;
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mode_map[kNumberTypeFloat16][kNumberTypeUInt8] = LaunchCast<float16, uint8_t>;
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mode_map[kNumberTypeFloat16][kNumberTypeUInt16] = LaunchCast<float16, uint16_t>;
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mode_map[kNumberTypeFloat16][kNumberTypeUInt32] = LaunchCast<float16, uint32_t>;
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mode_map[kNumberTypeFloat16][kNumberTypeUInt64] = LaunchCast<float16, uint64_t>;
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mode_map[kNumberTypeFloat16][kNumberTypeBool] = LaunchCast<float16, bool>;
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mode_map[kNumberTypeFloat32][kNumberTypeFloat16] = LaunchCast<float, float16>;
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mode_map[kNumberTypeFloat32][kNumberTypeFloat32] = LaunchCast<float, float>;
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mode_map[kNumberTypeFloat32][kNumberTypeFloat64] = LaunchCast<float, double>;
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mode_map[kNumberTypeFloat32][kNumberTypeInt8] = LaunchCast<float, int8_t>;
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mode_map[kNumberTypeFloat32][kNumberTypeInt16] = LaunchCast<float, int16_t>;
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mode_map[kNumberTypeFloat32][kNumberTypeInt32] = LaunchCast<float, int32_t>;
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mode_map[kNumberTypeFloat32][kNumberTypeInt64] = LaunchCast<float, int64_t>;
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mode_map[kNumberTypeFloat32][kNumberTypeUInt8] = LaunchCast<float, uint8_t>;
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mode_map[kNumberTypeFloat32][kNumberTypeUInt16] = LaunchCast<float, uint16_t>;
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mode_map[kNumberTypeFloat32][kNumberTypeUInt32] = LaunchCast<float, uint32_t>;
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mode_map[kNumberTypeFloat32][kNumberTypeUInt64] = LaunchCast<float, uint64_t>;
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mode_map[kNumberTypeFloat32][kNumberTypeBool] = LaunchCast<float, bool>;
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mode_map[kNumberTypeFloat64][kNumberTypeFloat16] = LaunchCast<double, float16>;
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mode_map[kNumberTypeFloat64][kNumberTypeFloat32] = LaunchCast<double, float>;
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mode_map[kNumberTypeFloat64][kNumberTypeFloat64] = LaunchCast<double, double>;
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mode_map[kNumberTypeFloat64][kNumberTypeInt8] = LaunchCast<double, int8_t>;
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mode_map[kNumberTypeFloat64][kNumberTypeInt16] = LaunchCast<double, int16_t>;
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mode_map[kNumberTypeFloat64][kNumberTypeInt32] = LaunchCast<double, int32_t>;
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mode_map[kNumberTypeFloat64][kNumberTypeInt64] = LaunchCast<double, int64_t>;
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mode_map[kNumberTypeFloat64][kNumberTypeUInt8] = LaunchCast<double, uint8_t>;
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mode_map[kNumberTypeFloat64][kNumberTypeUInt16] = LaunchCast<double, uint16_t>;
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mode_map[kNumberTypeFloat64][kNumberTypeUInt32] = LaunchCast<double, uint32_t>;
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mode_map[kNumberTypeFloat64][kNumberTypeUInt64] = LaunchCast<double, uint64_t>;
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mode_map[kNumberTypeFloat64][kNumberTypeBool] = LaunchCast<double, bool>;
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mode_map[kNumberTypeInt8][kNumberTypeFloat16] = LaunchCast<int8_t, float16>;
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mode_map[kNumberTypeInt8][kNumberTypeFloat32] = LaunchCast<int8_t, float>;
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mode_map[kNumberTypeInt8][kNumberTypeFloat64] = LaunchCast<int8_t, double>;
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mode_map[kNumberTypeInt8][kNumberTypeInt8] = LaunchCast<int8_t, int8_t>;
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mode_map[kNumberTypeInt8][kNumberTypeInt16] = LaunchCast<int8_t, int16_t>;
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mode_map[kNumberTypeInt8][kNumberTypeInt32] = LaunchCast<int8_t, int32_t>;
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mode_map[kNumberTypeInt8][kNumberTypeInt64] = LaunchCast<int8_t, int64_t>;
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mode_map[kNumberTypeInt8][kNumberTypeUInt8] = LaunchCast<int8_t, uint8_t>;
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mode_map[kNumberTypeInt8][kNumberTypeUInt16] = LaunchCast<int8_t, uint16_t>;
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mode_map[kNumberTypeInt8][kNumberTypeUInt32] = LaunchCast<int8_t, uint32_t>;
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mode_map[kNumberTypeInt8][kNumberTypeUInt64] = LaunchCast<int8_t, uint64_t>;
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mode_map[kNumberTypeInt8][kNumberTypeBool] = LaunchCast<int8_t, bool>;
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mode_map[kNumberTypeInt16][kNumberTypeFloat16] = LaunchCast<int16_t, float16>;
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mode_map[kNumberTypeInt16][kNumberTypeFloat32] = LaunchCast<int16_t, float>;
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mode_map[kNumberTypeInt16][kNumberTypeFloat64] = LaunchCast<int16_t, double>;
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mode_map[kNumberTypeInt16][kNumberTypeInt8] = LaunchCast<int16_t, int8_t>;
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mode_map[kNumberTypeInt16][kNumberTypeInt16] = LaunchCast<int16_t, int16_t>;
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mode_map[kNumberTypeInt16][kNumberTypeInt32] = LaunchCast<int16_t, int32_t>;
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mode_map[kNumberTypeInt16][kNumberTypeInt64] = LaunchCast<int16_t, int64_t>;
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mode_map[kNumberTypeInt16][kNumberTypeUInt8] = LaunchCast<int16_t, uint8_t>;
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mode_map[kNumberTypeInt16][kNumberTypeUInt16] = LaunchCast<int16_t, uint16_t>;
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mode_map[kNumberTypeInt16][kNumberTypeUInt32] = LaunchCast<int16_t, uint32_t>;
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mode_map[kNumberTypeInt16][kNumberTypeUInt64] = LaunchCast<int16_t, uint64_t>;
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mode_map[kNumberTypeInt16][kNumberTypeBool] = LaunchCast<int16_t, bool>;
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mode_map[kNumberTypeInt32][kNumberTypeFloat16] = LaunchCast<int32_t, float16>;
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mode_map[kNumberTypeInt32][kNumberTypeFloat32] = LaunchCast<int32_t, float>;
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mode_map[kNumberTypeInt32][kNumberTypeFloat64] = LaunchCast<int32_t, double>;
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mode_map[kNumberTypeInt32][kNumberTypeInt8] = LaunchCast<int32_t, int8_t>;
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mode_map[kNumberTypeInt32][kNumberTypeInt16] = LaunchCast<int32_t, int16_t>;
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mode_map[kNumberTypeInt32][kNumberTypeInt32] = LaunchCast<int32_t, int32_t>;
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mode_map[kNumberTypeInt32][kNumberTypeInt64] = LaunchCast<int32_t, int64_t>;
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mode_map[kNumberTypeInt32][kNumberTypeUInt8] = LaunchCast<int32_t, uint8_t>;
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mode_map[kNumberTypeInt32][kNumberTypeUInt16] = LaunchCast<int32_t, uint16_t>;
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mode_map[kNumberTypeInt32][kNumberTypeUInt32] = LaunchCast<int32_t, uint32_t>;
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mode_map[kNumberTypeInt32][kNumberTypeUInt64] = LaunchCast<int32_t, uint64_t>;
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mode_map[kNumberTypeInt32][kNumberTypeBool] = LaunchCast<int32_t, bool>;
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mode_map[kNumberTypeInt64][kNumberTypeFloat16] = LaunchCast<int64_t, float16>;
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mode_map[kNumberTypeInt64][kNumberTypeFloat32] = LaunchCast<int64_t, float>;
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mode_map[kNumberTypeInt64][kNumberTypeFloat64] = LaunchCast<int64_t, double>;
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mode_map[kNumberTypeInt64][kNumberTypeInt8] = LaunchCast<int64_t, int8_t>;
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mode_map[kNumberTypeInt64][kNumberTypeInt16] = LaunchCast<int64_t, int16_t>;
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mode_map[kNumberTypeInt64][kNumberTypeInt32] = LaunchCast<int64_t, int32_t>;
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mode_map[kNumberTypeInt64][kNumberTypeInt64] = LaunchCast<int64_t, int64_t>;
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mode_map[kNumberTypeInt64][kNumberTypeUInt8] = LaunchCast<int64_t, uint8_t>;
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mode_map[kNumberTypeInt64][kNumberTypeUInt16] = LaunchCast<int64_t, uint16_t>;
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mode_map[kNumberTypeInt64][kNumberTypeUInt32] = LaunchCast<int64_t, uint32_t>;
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mode_map[kNumberTypeInt64][kNumberTypeUInt64] = LaunchCast<int64_t, uint64_t>;
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mode_map[kNumberTypeInt64][kNumberTypeBool] = LaunchCast<int64_t, bool>;
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mode_map[kNumberTypeUInt8][kNumberTypeFloat16] = LaunchCast<uint8_t, float16>;
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mode_map[kNumberTypeUInt8][kNumberTypeFloat32] = LaunchCast<uint8_t, float>;
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mode_map[kNumberTypeUInt8][kNumberTypeFloat64] = LaunchCast<uint8_t, double>;
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mode_map[kNumberTypeUInt8][kNumberTypeInt8] = LaunchCast<uint8_t, int8_t>;
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mode_map[kNumberTypeUInt8][kNumberTypeInt16] = LaunchCast<uint8_t, int16_t>;
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mode_map[kNumberTypeUInt8][kNumberTypeInt32] = LaunchCast<uint8_t, int32_t>;
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mode_map[kNumberTypeUInt8][kNumberTypeInt64] = LaunchCast<uint8_t, int64_t>;
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mode_map[kNumberTypeUInt8][kNumberTypeUInt8] = LaunchCast<uint8_t, uint8_t>;
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mode_map[kNumberTypeUInt8][kNumberTypeUInt16] = LaunchCast<uint8_t, uint16_t>;
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mode_map[kNumberTypeUInt8][kNumberTypeUInt32] = LaunchCast<uint8_t, uint32_t>;
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mode_map[kNumberTypeUInt8][kNumberTypeUInt64] = LaunchCast<uint8_t, uint64_t>;
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mode_map[kNumberTypeUInt8][kNumberTypeBool] = LaunchCast<uint8_t, bool>;
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mode_map[kNumberTypeInt16][kNumberTypeInt32] = LaunchCast<int16_t, int32_t>;
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mode_map[kNumberTypeInt16][kNumberTypeInt64] = LaunchCast<int16_t, int64_t>;
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mode_map[kNumberTypeUInt16][kNumberTypeFloat16] = LaunchCast<uint16_t, float16>;
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mode_map[kNumberTypeUInt16][kNumberTypeFloat32] = LaunchCast<uint16_t, float>;
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mode_map[kNumberTypeUInt16][kNumberTypeFloat64] = LaunchCast<uint16_t, double>;
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mode_map[kNumberTypeUInt16][kNumberTypeInt8] = LaunchCast<uint16_t, int8_t>;
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mode_map[kNumberTypeUInt16][kNumberTypeInt16] = LaunchCast<uint16_t, int16_t>;
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mode_map[kNumberTypeUInt16][kNumberTypeInt32] = LaunchCast<uint16_t, int32_t>;
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mode_map[kNumberTypeUInt16][kNumberTypeInt64] = LaunchCast<uint16_t, int64_t>;
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mode_map[kNumberTypeUInt16][kNumberTypeUInt8] = LaunchCast<uint16_t, uint8_t>;
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mode_map[kNumberTypeUInt16][kNumberTypeUInt16] = LaunchCast<uint16_t, uint16_t>;
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mode_map[kNumberTypeUInt16][kNumberTypeUInt32] = LaunchCast<uint16_t, uint32_t>;
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mode_map[kNumberTypeUInt16][kNumberTypeUInt64] = LaunchCast<uint16_t, uint64_t>;
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mode_map[kNumberTypeUInt16][kNumberTypeBool] = LaunchCast<uint16_t, bool>;
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mode_map[kNumberTypeInt32][kNumberTypeInt64] = LaunchCast<int32_t, int64_t>;
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mode_map[kNumberTypeUInt32][kNumberTypeFloat16] = LaunchCast<uint32_t, float16>;
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mode_map[kNumberTypeUInt32][kNumberTypeFloat32] = LaunchCast<uint32_t, float>;
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mode_map[kNumberTypeUInt32][kNumberTypeFloat64] = LaunchCast<uint32_t, double>;
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mode_map[kNumberTypeUInt32][kNumberTypeInt8] = LaunchCast<uint32_t, int8_t>;
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mode_map[kNumberTypeUInt32][kNumberTypeInt16] = LaunchCast<uint32_t, int16_t>;
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mode_map[kNumberTypeUInt32][kNumberTypeInt32] = LaunchCast<uint32_t, int32_t>;
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mode_map[kNumberTypeUInt32][kNumberTypeInt64] = LaunchCast<uint32_t, int64_t>;
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mode_map[kNumberTypeUInt32][kNumberTypeUInt8] = LaunchCast<uint32_t, uint8_t>;
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mode_map[kNumberTypeUInt32][kNumberTypeUInt16] = LaunchCast<uint32_t, uint16_t>;
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mode_map[kNumberTypeUInt32][kNumberTypeUInt32] = LaunchCast<uint32_t, uint32_t>;
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mode_map[kNumberTypeUInt32][kNumberTypeUInt64] = LaunchCast<uint32_t, uint64_t>;
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mode_map[kNumberTypeUInt32][kNumberTypeBool] = LaunchCast<uint32_t, bool>;
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mode_map[kNumberTypeUInt64][kNumberTypeFloat16] = LaunchCast<uint64_t, float16>;
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mode_map[kNumberTypeUInt64][kNumberTypeFloat32] = LaunchCast<uint64_t, float>;
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mode_map[kNumberTypeUInt64][kNumberTypeFloat64] = LaunchCast<uint64_t, double>;
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mode_map[kNumberTypeUInt64][kNumberTypeInt8] = LaunchCast<uint64_t, int8_t>;
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mode_map[kNumberTypeUInt64][kNumberTypeInt16] = LaunchCast<uint64_t, int16_t>;
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mode_map[kNumberTypeUInt64][kNumberTypeInt32] = LaunchCast<uint64_t, int32_t>;
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mode_map[kNumberTypeUInt64][kNumberTypeInt64] = LaunchCast<uint64_t, int64_t>;
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mode_map[kNumberTypeUInt64][kNumberTypeUInt8] = LaunchCast<uint64_t, uint8_t>;
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mode_map[kNumberTypeUInt64][kNumberTypeUInt16] = LaunchCast<uint64_t, uint16_t>;
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mode_map[kNumberTypeUInt64][kNumberTypeUInt32] = LaunchCast<uint64_t, uint32_t>;
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mode_map[kNumberTypeUInt64][kNumberTypeUInt64] = LaunchCast<uint64_t, uint64_t>;
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mode_map[kNumberTypeUInt64][kNumberTypeBool] = LaunchCast<uint64_t, bool>;
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mode_map[kNumberTypeFloat16][kNumberTypeFloat32] = LaunchCast<float16, float>;
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mode_map[kNumberTypeFloat16][kNumberTypeFloat64] = LaunchCast<float16, double>;
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mode_map[kNumberTypeFloat32][kNumberTypeFloat64] = LaunchCast<float, double>;
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mode_map[source_dtype][target_dtype](inputs, outputs);
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return true;
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}
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@ -38,40 +38,161 @@ class CastCPUKernel : public CPUKernel {
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TypeId target_dtype{kTypeUnknown};
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};
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeInt32), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeBool), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeInt32), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeFloat32), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeBool), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeBool).AddOutputAttr(kNumberTypeBool), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeBool).AddOutputAttr(kNumberTypeInt32), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeBool).AddOutputAttr(kNumberTypeFloat16), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeBool).AddOutputAttr(kNumberTypeFloat32), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeBool).AddOutputAttr(kNumberTypeFloat64), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeBool).AddOutputAttr(kNumberTypeInt8), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeBool).AddOutputAttr(kNumberTypeInt16), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeBool).AddOutputAttr(kNumberTypeInt32), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeBool).AddOutputAttr(kNumberTypeInt64), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeBool).AddOutputAttr(kNumberTypeUInt8), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeBool).AddOutputAttr(kNumberTypeUInt16), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeBool).AddOutputAttr(kNumberTypeUInt32), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeBool).AddOutputAttr(kNumberTypeUInt64), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeBool).AddOutputAttr(kNumberTypeBool), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat32), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat64), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeInt8), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeInt16), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeInt32), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeInt64), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeUInt8), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeUInt16), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeUInt32), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeUInt64), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeBool), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat16), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat64), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeInt8), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeInt16), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeInt32), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeInt64), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeUInt8), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeUInt16), CastCPUKernel);
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MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeUInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeUInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeBool), CastCPUKernel);
|
||||
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat64).AddOutputAttr(kNumberTypeFloat16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat64).AddOutputAttr(kNumberTypeFloat32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat64).AddOutputAttr(kNumberTypeFloat64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat64).AddOutputAttr(kNumberTypeInt8), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat64).AddOutputAttr(kNumberTypeInt16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat64).AddOutputAttr(kNumberTypeInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat64).AddOutputAttr(kNumberTypeInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat64).AddOutputAttr(kNumberTypeUInt8), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat64).AddOutputAttr(kNumberTypeUInt16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat64).AddOutputAttr(kNumberTypeUInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat64).AddOutputAttr(kNumberTypeUInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat64).AddOutputAttr(kNumberTypeBool), CastCPUKernel);
|
||||
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt8).AddOutputAttr(kNumberTypeFloat16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt8).AddOutputAttr(kNumberTypeFloat32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt8).AddOutputAttr(kNumberTypeFloat64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt8).AddOutputAttr(kNumberTypeInt8), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt8).AddOutputAttr(kNumberTypeInt16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt8).AddOutputAttr(kNumberTypeInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt8).AddOutputAttr(kNumberTypeInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt8).AddOutputAttr(kNumberTypeUInt8), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt8).AddOutputAttr(kNumberTypeUInt16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt8).AddOutputAttr(kNumberTypeUInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt8).AddOutputAttr(kNumberTypeUInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt8).AddOutputAttr(kNumberTypeBool), CastCPUKernel);
|
||||
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt16).AddOutputAttr(kNumberTypeFloat16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt16).AddOutputAttr(kNumberTypeFloat32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt16).AddOutputAttr(kNumberTypeFloat64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt16).AddOutputAttr(kNumberTypeInt8), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt16).AddOutputAttr(kNumberTypeInt16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt16).AddOutputAttr(kNumberTypeInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt16).AddOutputAttr(kNumberTypeInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt16).AddOutputAttr(kNumberTypeUInt8), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt16).AddOutputAttr(kNumberTypeUInt16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt16).AddOutputAttr(kNumberTypeUInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt16).AddOutputAttr(kNumberTypeUInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt16).AddOutputAttr(kNumberTypeBool), CastCPUKernel);
|
||||
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeFloat16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeFloat32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeFloat64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeInt8), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeInt16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeUInt8), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeUInt16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeUInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeUInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeBool), CastCPUKernel);
|
||||
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt64).AddOutputAttr(kNumberTypeFloat16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt64).AddOutputAttr(kNumberTypeFloat32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt64).AddOutputAttr(kNumberTypeFloat64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt64).AddOutputAttr(kNumberTypeInt8), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt64).AddOutputAttr(kNumberTypeInt16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt64).AddOutputAttr(kNumberTypeInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt64).AddOutputAttr(kNumberTypeInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt64).AddOutputAttr(kNumberTypeUInt8), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt64).AddOutputAttr(kNumberTypeUInt16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt64).AddOutputAttr(kNumberTypeUInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt64).AddOutputAttr(kNumberTypeUInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt64).AddOutputAttr(kNumberTypeBool), CastCPUKernel);
|
||||
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt8).AddOutputAttr(kNumberTypeFloat16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt8).AddOutputAttr(kNumberTypeFloat32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt8).AddOutputAttr(kNumberTypeFloat64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt8).AddOutputAttr(kNumberTypeInt8), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt8).AddOutputAttr(kNumberTypeInt16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt8).AddOutputAttr(kNumberTypeInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt8).AddOutputAttr(kNumberTypeInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt8).AddOutputAttr(kNumberTypeUInt8), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt8).AddOutputAttr(kNumberTypeUInt16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt8).AddOutputAttr(kNumberTypeUInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt8).AddOutputAttr(kNumberTypeUInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt8).AddOutputAttr(kNumberTypeBool), CastCPUKernel);
|
||||
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt16).AddOutputAttr(kNumberTypeInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt16).AddOutputAttr(kNumberTypeInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt16).AddOutputAttr(kNumberTypeFloat16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt16).AddOutputAttr(kNumberTypeFloat32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt16).AddOutputAttr(kNumberTypeFloat64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt16).AddOutputAttr(kNumberTypeInt8), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt16).AddOutputAttr(kNumberTypeInt16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt16).AddOutputAttr(kNumberTypeInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt16).AddOutputAttr(kNumberTypeInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt16).AddOutputAttr(kNumberTypeUInt8), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt16).AddOutputAttr(kNumberTypeUInt16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt16).AddOutputAttr(kNumberTypeUInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt16).AddOutputAttr(kNumberTypeUInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt16).AddOutputAttr(kNumberTypeBool), CastCPUKernel);
|
||||
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeInt32).AddOutputAttr(kNumberTypeInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt32).AddOutputAttr(kNumberTypeFloat16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt32).AddOutputAttr(kNumberTypeFloat32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt32).AddOutputAttr(kNumberTypeFloat64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt32).AddOutputAttr(kNumberTypeInt8), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt32).AddOutputAttr(kNumberTypeInt16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt32).AddOutputAttr(kNumberTypeInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt32).AddOutputAttr(kNumberTypeInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt32).AddOutputAttr(kNumberTypeUInt8), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt32).AddOutputAttr(kNumberTypeUInt16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt32).AddOutputAttr(kNumberTypeUInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt32).AddOutputAttr(kNumberTypeUInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt32).AddOutputAttr(kNumberTypeBool), CastCPUKernel);
|
||||
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt64).AddOutputAttr(kNumberTypeFloat16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt64).AddOutputAttr(kNumberTypeFloat32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt64).AddOutputAttr(kNumberTypeFloat64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt64).AddOutputAttr(kNumberTypeInt8), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt64).AddOutputAttr(kNumberTypeInt16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt64).AddOutputAttr(kNumberTypeInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt64).AddOutputAttr(kNumberTypeInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt64).AddOutputAttr(kNumberTypeUInt8), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt64).AddOutputAttr(kNumberTypeUInt16), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt64).AddOutputAttr(kNumberTypeUInt32), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt64).AddOutputAttr(kNumberTypeUInt64), CastCPUKernel);
|
||||
MS_REG_CPU_KERNEL(Cast, KernelAttr().AddInputAttr(kNumberTypeUInt64).AddOutputAttr(kNumberTypeBool), CastCPUKernel);
|
||||
} // namespace kernel
|
||||
} // namespace mindspore
|
||||
|
||||
|
|
|
|||
|
|
@ -36,314 +36,299 @@ class Net(Cell):
|
|||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_int32():
|
||||
x0 = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32))
|
||||
x1 = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32))
|
||||
x2 = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool))
|
||||
t = mstype.int32
|
||||
def test_cast_bool():
|
||||
tensor_to_cast = []
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
|
||||
t = mstype.bool_
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x0)
|
||||
type0 = output.asnumpy().dtype
|
||||
assert type0 == 'int32'
|
||||
output = net(x1)
|
||||
type1 = output.asnumpy().dtype
|
||||
assert type1 == 'int32'
|
||||
output = net(x2)
|
||||
type2 = output.asnumpy().dtype
|
||||
assert type2 == 'int32'
|
||||
for tensor in tensor_to_cast:
|
||||
net = Net(t)
|
||||
output = net(tensor)
|
||||
assert output.asnumpy().dtype == 'bool'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_float16():
|
||||
tensor_to_cast = []
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
|
||||
t = mstype.float16
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
for tensor in tensor_to_cast:
|
||||
net = Net(t)
|
||||
output = net(tensor)
|
||||
assert output.asnumpy().dtype == 'float16'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_float32():
|
||||
x0 = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32))
|
||||
x1 = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32))
|
||||
x2 = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool))
|
||||
tensor_to_cast = []
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
|
||||
t = mstype.float32
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x0)
|
||||
type0 = output.asnumpy().dtype
|
||||
assert type0 == 'float32'
|
||||
output = net(x1)
|
||||
type1 = output.asnumpy().dtype
|
||||
assert type1 == 'float32'
|
||||
output = net(x2)
|
||||
type2 = output.asnumpy().dtype
|
||||
assert type2 == 'float32'
|
||||
for tensor in tensor_to_cast:
|
||||
net = Net(t)
|
||||
output = net(tensor)
|
||||
assert output.asnumpy().dtype == 'float32'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_int8_to_int16():
|
||||
x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8))
|
||||
def test_cast_float64():
|
||||
tensor_to_cast = []
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
|
||||
t = mstype.float64
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
for tensor in tensor_to_cast:
|
||||
net = Net(t)
|
||||
output = net(tensor)
|
||||
assert output.asnumpy().dtype == 'float64'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_int8():
|
||||
tensor_to_cast = []
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
|
||||
t = mstype.int8
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
for tensor in tensor_to_cast:
|
||||
net = Net(t)
|
||||
output = net(tensor)
|
||||
assert output.asnumpy().dtype == 'int8'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_int16():
|
||||
tensor_to_cast = []
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
|
||||
t = mstype.int16
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x)
|
||||
dtype = output.asnumpy().dtype
|
||||
assert dtype == 'int16'
|
||||
for tensor in tensor_to_cast:
|
||||
net = Net(t)
|
||||
output = net(tensor)
|
||||
assert output.asnumpy().dtype == 'int16'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_int8_to_int32():
|
||||
x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8))
|
||||
def test_cast_int32():
|
||||
tensor_to_cast = []
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
|
||||
t = mstype.int32
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x)
|
||||
dtype = output.asnumpy().dtype
|
||||
assert dtype == 'int32'
|
||||
for tensor in tensor_to_cast:
|
||||
net = Net(t)
|
||||
output = net(tensor)
|
||||
assert output.asnumpy().dtype == 'int32'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_int8_to_int64():
|
||||
x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8))
|
||||
def test_cast_int64():
|
||||
tensor_to_cast = []
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
|
||||
t = mstype.int64
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x)
|
||||
dtype = output.asnumpy().dtype
|
||||
assert dtype == 'int64'
|
||||
for tensor in tensor_to_cast:
|
||||
net = Net(t)
|
||||
output = net(tensor)
|
||||
assert output.asnumpy().dtype == 'int64'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_uint8_to_int16():
|
||||
x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8))
|
||||
t = mstype.int16
|
||||
def test_cast_uint8():
|
||||
tensor_to_cast = []
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
|
||||
t = mstype.uint8
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x)
|
||||
dtype = output.asnumpy().dtype
|
||||
assert dtype == 'int16'
|
||||
for tensor in tensor_to_cast:
|
||||
net = Net(t)
|
||||
output = net(tensor)
|
||||
assert output.asnumpy().dtype == 'uint8'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_uint8_to_int32():
|
||||
x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8))
|
||||
t = mstype.int32
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x)
|
||||
dtype = output.asnumpy().dtype
|
||||
assert dtype == 'int32'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_uint8_to_int64():
|
||||
x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8))
|
||||
t = mstype.int64
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x)
|
||||
dtype = output.asnumpy().dtype
|
||||
assert dtype == 'int64'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_uint8_to_uint16():
|
||||
x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8))
|
||||
def test_cast_uint16():
|
||||
tensor_to_cast = []
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
|
||||
t = mstype.uint16
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x)
|
||||
dtype = output.asnumpy().dtype
|
||||
assert dtype == 'uint16'
|
||||
for tensor in tensor_to_cast:
|
||||
net = Net(t)
|
||||
output = net(tensor)
|
||||
assert output.asnumpy().dtype == 'uint16'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_uint8_to_uint32():
|
||||
x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8))
|
||||
def test_cast_uint32():
|
||||
tensor_to_cast = []
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
|
||||
t = mstype.uint32
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x)
|
||||
dtype = output.asnumpy().dtype
|
||||
assert dtype == 'uint32'
|
||||
for tensor in tensor_to_cast:
|
||||
net = Net(t)
|
||||
output = net(tensor)
|
||||
assert output.asnumpy().dtype == 'uint32'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_uint8_to_uint64():
|
||||
x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8))
|
||||
def test_cast_uint64():
|
||||
tensor_to_cast = []
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.bool)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int64)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint8)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32)))
|
||||
tensor_to_cast.append(Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint64)))
|
||||
t = mstype.uint64
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x)
|
||||
dtype = output.asnumpy().dtype
|
||||
assert dtype == 'uint64'
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|
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
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@pytest.mark.env_onecard
|
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def test_cast_int16_to_int32():
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x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16))
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t = mstype.int32
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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net = Net(t)
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output = net(x)
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dtype = output.asnumpy().dtype
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assert dtype == 'int32'
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|
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@pytest.mark.level0
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@pytest.mark.platform_x86_cpu
|
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@pytest.mark.env_onecard
|
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def test_cast_int16_to_int64():
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x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int16))
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t = mstype.int64
|
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|
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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net = Net(t)
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output = net(x)
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dtype = output.asnumpy().dtype
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assert dtype == 'int64'
|
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|
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@pytest.mark.level0
|
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@pytest.mark.platform_x86_cpu
|
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@pytest.mark.env_onecard
|
||||
def test_cast_uint16_to_int32():
|
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x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16))
|
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t = mstype.int32
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
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net = Net(t)
|
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output = net(x)
|
||||
dtype = output.asnumpy().dtype
|
||||
assert dtype == 'int32'
|
||||
|
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@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_uint16_to_int64():
|
||||
x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16))
|
||||
t = mstype.int64
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x)
|
||||
dtype = output.asnumpy().dtype
|
||||
assert dtype == 'int64'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_uint16_to_uint32():
|
||||
x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16))
|
||||
t = mstype.uint32
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x)
|
||||
dtype = output.asnumpy().dtype
|
||||
assert dtype == 'uint32'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_uint16_to_uint64():
|
||||
x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint16))
|
||||
t = mstype.uint64
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x)
|
||||
dtype = output.asnumpy().dtype
|
||||
assert dtype == 'uint64'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_int32_to_int64():
|
||||
x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.int32))
|
||||
t = mstype.int64
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x)
|
||||
dtype = output.asnumpy().dtype
|
||||
assert dtype == 'int64'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_uint32_to_int64():
|
||||
x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32))
|
||||
t = mstype.int64
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x)
|
||||
dtype = output.asnumpy().dtype
|
||||
assert dtype == 'int64'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_uint32_to_uint64():
|
||||
x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.uint32))
|
||||
t = mstype.uint64
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x)
|
||||
dtype = output.asnumpy().dtype
|
||||
assert dtype == 'uint64'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_float16_to_float32():
|
||||
x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16))
|
||||
t = mstype.float32
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x)
|
||||
dtype = output.asnumpy().dtype
|
||||
assert dtype == 'float32'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_float16_to_float64():
|
||||
x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float16))
|
||||
t = mstype.float64
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x)
|
||||
dtype = output.asnumpy().dtype
|
||||
assert dtype == 'float64'
|
||||
|
||||
@pytest.mark.level0
|
||||
@pytest.mark.platform_x86_cpu
|
||||
@pytest.mark.env_onecard
|
||||
def test_cast_float32_to_float64():
|
||||
x = Tensor(np.random.uniform(-2, 2, (3, 2)).astype(np.float32))
|
||||
t = mstype.float64
|
||||
|
||||
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
||||
net = Net(t)
|
||||
output = net(x)
|
||||
dtype = output.asnumpy().dtype
|
||||
assert dtype == 'float64'
|
||||
for tensor in tensor_to_cast:
|
||||
net = Net(t)
|
||||
output = net(tensor)
|
||||
assert output.asnumpy().dtype == 'uint64'
|
||||
|
|
|
|||
Loading…
Reference in New Issue