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Add dtype float16 that erf and erfc should support

This commit is contained in:
peixu_ren 2020-09-16 14:31:22 -04:00
parent 6f5be6b876
commit 8132e56417
6 changed files with 34 additions and 6 deletions
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3
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/erf_impl.cu
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@ -18,7 +18,7 @@
template <typename T>
__global__ void ErfKernel(T *input, T *output, size_t count) {
for (size_t i = blockIdx.x * blockDim.x + threadIdx.x; i < (count); i += blockDim.x * gridDim.x) {
output[i] = (T)erf(input[i]);
output[i] = static_cast<T>(erf(static_cast<float>(input[i])));
}
return;
}
@ -30,3 +30,4 @@ void Erf(T *input, T *output, size_t count, cudaStream_t cuda_stream) {
}
template void Erf<float>(float *input, float *output, size_t count, cudaStream_t cuda_stream);
template void Erf<half>(half *input, half *output, size_t count, cudaStream_t cuda_stream);

3
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/erfc_impl.cu
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@ -18,7 +18,7 @@
template <typename T>
__global__ void ErfcKernel(T *input, T *output, size_t count) {
for (size_t i = blockIdx.x * blockDim.x + threadIdx.x; i < (count); i += blockDim.x * gridDim.x) {
output[i] = (T)erfc(input[i]);
output[i] = static_cast<T>(erfc(static_cast<float>(input[i])));
}
return;
}
@ -30,3 +30,4 @@ void Erfc(T *input, T *output, size_t count, cudaStream_t cuda_stream) {
}
template void Erfc<float>(float *input, float *output, size_t count, cudaStream_t cuda_stream);
template void Erfc<half>(half *input, half *output, size_t count, cudaStream_t cuda_stream);

2
mindspore/ccsrc/backend/kernel_compiler/gpu/math/erf_gpu_kernel.cc
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@ -20,5 +20,7 @@ namespace mindspore {
namespace kernel {
MS_REG_GPU_KERNEL_ONE(Erf, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
ErfGpuKernel, float)
MS_REG_GPU_KERNEL_ONE(Erf, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
ErfGpuKernel, half)
} // namespace kernel
} // namespace mindspore

2
mindspore/ccsrc/backend/kernel_compiler/gpu/math/erfc_gpu_kernel.cc
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@ -20,5 +20,7 @@ namespace mindspore {
namespace kernel {
MS_REG_GPU_KERNEL_ONE(Erfc, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
ErfcGpuKernel, float)
MS_REG_GPU_KERNEL_ONE(Erfc, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
ErfcGpuKernel, half)
} // namespace kernel
} // namespace mindspore

15
tests/st/ops/gpu/test_erf_op.py
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@ -37,10 +37,21 @@ class NetErf(nn.Cell):
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
def test_exp():
def test_erf_fp32():
erf = NetErf()
x = np.array([2.0, 3.0, 4.0, 5.0]).astype(np.float32)
x = np.random.rand(3, 8).astype(np.float32)
output = erf(Tensor(x, dtype=dtype.float32))
expect = special.erf(x)
tol = 1e-6
assert (np.abs(output.asnumpy() - expect) < tol).all()
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
def test_erf_fp16():
erf = NetErf()
x = np.random.rand(3, 8).astype(np.float16)
output = erf(Tensor(x, dtype=dtype.float16))
expect = special.erf(x)
tol = 1e-3
assert (np.abs(output.asnumpy() - expect) < tol).all()

15
tests/st/ops/gpu/test_erfc_op.py
View File

@ -37,10 +37,21 @@ class NetErfc(nn.Cell):
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
def test_exp():
def test_erfc_fp32():
erfc = NetErfc()
x = np.array([2.0, 3.0, 4.0, 5.0]).astype(np.float32)
x = np.random.rand(3, 8).astype(np.float32)
output = erfc(Tensor(x, dtype=dtype.float32))
expect = special.erfc(x)
tol = 1e-6
assert (np.abs(output.asnumpy() - expect) < tol).all()
@pytest.mark.level0
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
def test_erfc_fp16():
erfc = NetErfc()
x = np.random.rand(3, 8).astype(np.float16)
output = erfc(Tensor(x, dtype=dtype.float16))
expect = special.erfc(x)
tol = 1e-3
assert (np.abs(output.asnumpy() - expect) < tol).all()