!13705 Update CPU Supported OPS

From: @wuxuejian
Reviewed-by: @liangchenghui,@kisnwang
Signed-off-by: @liangchenghui
This commit is contained in:
mindspore-ci-bot 2021-03-22 15:56:33 +08:00 committed by Gitee
commit 9ae264f32a
3 changed files with 19 additions and 19 deletions

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@ -642,7 +642,7 @@ class Squeeze(PrimitiveWithInfer):
ValueError: If the corresponding dimension of the specified axis does not equal to 1. ValueError: If the corresponding dimension of the specified axis does not equal to 1.
Supported Platforms: Supported Platforms:
``Ascend`` ``GPU`` ``Ascend`` ``GPU`` ``CPU``
Examples: Examples:
>>> input_tensor = Tensor(np.ones(shape=[3, 2, 1]), mindspore.float32) >>> input_tensor = Tensor(np.ones(shape=[3, 2, 1]), mindspore.float32)
@ -1984,7 +1984,7 @@ class UnsortedSegmentSum(PrimitiveWithInfer):
ValueError: If length of shape of `segment_ids` is less than 1. ValueError: If length of shape of `segment_ids` is less than 1.
Supported Platforms: Supported Platforms:
``Ascend`` ``GPU`` ``Ascend`` ``GPU`` ``CPU``
Examples: Examples:
>>> input_x = Tensor([1, 2, 3, 4], mindspore.float32) >>> input_x = Tensor([1, 2, 3, 4], mindspore.float32)
@ -5239,7 +5239,7 @@ class Range(PrimitiveWithCheck):
[0, 4, 8] [0, 4, 8]
Supported Platforms: Supported Platforms:
``GPU`` ``GPU`` ``CPU``
""" """
@prim_attr_register @prim_attr_register

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@ -2658,7 +2658,7 @@ class Acosh(PrimitiveWithInfer):
TypeError: If `input_x` is not a Tensor. TypeError: If `input_x` is not a Tensor.
Supported Platforms: Supported Platforms:
``Ascend`` ``GPU`` ``Ascend`` ``GPU`` ``CPU``
Examples: Examples:
>>> acosh = ops.Acosh() >>> acosh = ops.Acosh()
@ -2735,7 +2735,7 @@ class Asinh(PrimitiveWithInfer):
TypeError: If `input_x` is not a Tensor. TypeError: If `input_x` is not a Tensor.
Supported Platforms: Supported Platforms:
``Ascend`` ``GPU`` ``Ascend`` ``GPU`` ``CPU``
Examples: Examples:
>>> asinh = ops.Asinh() >>> asinh = ops.Asinh()

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@ -664,7 +664,7 @@ class HSwish(PrimitiveWithInfer):
TypeError: If dtype of `input_data` is neither float16 nor float32. TypeError: If dtype of `input_data` is neither float16 nor float32.
Supported Platforms: Supported Platforms:
``GPU`` ``GPU`` ``CPU``
Examples: Examples:
>>> hswish = ops.HSwish() >>> hswish = ops.HSwish()
@ -708,7 +708,7 @@ class Sigmoid(PrimitiveWithInfer):
TypeError: If `input_x` is not a Tensor. TypeError: If `input_x` is not a Tensor.
Supported Platforms: Supported Platforms:
``Ascend`` ``GPU`` ``Ascend`` ``GPU`` ``CPU``
Examples: Examples:
>>> input_x = Tensor(np.array([1, 2, 3, 4, 5]), mindspore.float32) >>> input_x = Tensor(np.array([1, 2, 3, 4, 5]), mindspore.float32)
@ -754,7 +754,7 @@ class HSigmoid(PrimitiveWithInfer):
TypeError: If dtype of `input_data` is neither float16 nor float32. TypeError: If dtype of `input_data` is neither float16 nor float32.
Supported Platforms: Supported Platforms:
``GPU`` ``GPU`` ``CPU``
Examples: Examples:
>>> hsigmoid = ops.HSigmoid() >>> hsigmoid = ops.HSigmoid()
@ -1158,7 +1158,7 @@ class BatchNorm(PrimitiveWithInfer):
TypeError: If dtype of `input_x`, `scale` or `mean` is neither float16 nor float32. TypeError: If dtype of `input_x`, `scale` or `mean` is neither float16 nor float32.
Supported Platforms: Supported Platforms:
``Ascend`` ``Ascend`` ``CPU``
Examples: Examples:
>>> input_x = Tensor(np.ones([2, 2]), mindspore.float32) >>> input_x = Tensor(np.ones([2, 2]), mindspore.float32)
@ -1940,7 +1940,7 @@ class Conv2DBackpropInput(PrimitiveWithInfer):
ValueError: If `data_format` is neither 'NCHW' not 'NHWC'. ValueError: If `data_format` is neither 'NCHW' not 'NHWC'.
Supported Platforms: Supported Platforms:
``Ascend`` ``GPU`` ``Ascend`` ``GPU`` ``CPU``
Examples: Examples:
>>> dout = Tensor(np.ones([10, 32, 30, 30]), mindspore.float32) >>> dout = Tensor(np.ones([10, 32, 30, 30]), mindspore.float32)
@ -2482,7 +2482,7 @@ class SmoothL1Loss(PrimitiveWithInfer):
ValueError: If shape of `prediction` is not the same as `target`. ValueError: If shape of `prediction` is not the same as `target`.
Supported Platforms: Supported Platforms:
``Ascend`` ``GPU`` ``Ascend`` ``GPU`` ``CPU``
Examples: Examples:
>>> loss = ops.SmoothL1Loss() >>> loss = ops.SmoothL1Loss()
@ -2795,7 +2795,7 @@ class ApplyRMSProp(PrimitiveWithInfer):
ValueError: If `decay`, `momentum` or `epsilon` is not a constant value. ValueError: If `decay`, `momentum` or `epsilon` is not a constant value.
Supported Platforms: Supported Platforms:
``Ascend`` ``GPU`` ``Ascend`` ``GPU`` ``CPU``
Examples: Examples:
>>> apply_rms = ops.ApplyRMSProp() >>> apply_rms = ops.ApplyRMSProp()
@ -2898,7 +2898,7 @@ class ApplyCenteredRMSProp(PrimitiveWithInfer):
TypeError: If dtype of `decay`, `momentum` or `epsilon` is not float. TypeError: If dtype of `decay`, `momentum` or `epsilon` is not float.
Supported Platforms: Supported Platforms:
``Ascend`` ``GPU`` ``Ascend`` ``GPU`` ``CPU``
Examples: Examples:
>>> centered_rms_prop = ops.ApplyCenteredRMSProp() >>> centered_rms_prop = ops.ApplyCenteredRMSProp()
@ -2987,7 +2987,7 @@ class LayerNorm(Primitive):
TypeError: If `input_x`, `gamma` or `beta` is not a Tensor. TypeError: If `input_x`, `gamma` or `beta` is not a Tensor.
Supported Platforms: Supported Platforms:
``Ascend`` ``GPU`` ``Ascend`` ``GPU`` ``CPU``
Examples: Examples:
>>> input_x = Tensor(np.array([[1, 2, 3], [1, 2, 3]]), mindspore.float32) >>> input_x = Tensor(np.array([[1, 2, 3], [1, 2, 3]]), mindspore.float32)
@ -3367,7 +3367,7 @@ class GeLU(PrimitiveWithInfer):
TypeError: If dtype of `input_x` is neither float16 nor float32. TypeError: If dtype of `input_x` is neither float16 nor float32.
Supported Platforms: Supported Platforms:
``Ascend`` ``GPU`` ``Ascend`` ``GPU`` ``CPU``
Examples: Examples:
>>> tensor = Tensor(np.array([1.0, 2.0, 3.0]), mindspore.float32) >>> tensor = Tensor(np.array([1.0, 2.0, 3.0]), mindspore.float32)
@ -3868,7 +3868,7 @@ class Pad(PrimitiveWithInfer):
ValueError: If shape of `paddings` is not (n, 2). ValueError: If shape of `paddings` is not (n, 2).
Supported Platforms: Supported Platforms:
``Ascend`` ``GPU`` ``Ascend`` ``GPU`` ``CPU``
Examples: Examples:
>>> input_tensor = Tensor(np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]), mindspore.float32) >>> input_tensor = Tensor(np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]), mindspore.float32)
@ -3940,7 +3940,7 @@ class MirrorPad(PrimitiveWithInfer):
TypeError: If `mode` is not a str. TypeError: If `mode` is not a str.
Supported Platforms: Supported Platforms:
``Ascend`` ``GPU`` ``Ascend`` ``GPU`` ``CPU``
Examples: Examples:
>>> from mindspore import Tensor >>> from mindspore import Tensor
@ -4193,7 +4193,7 @@ class Adam(PrimitiveWithInfer):
TypeError: If `beta1_power`, `beta2_power1`, `lr`, `beta1`, `beta2`, `epsilon` or `gradient` is not a Tensor. TypeError: If `beta1_power`, `beta2_power1`, `lr`, `beta1`, `beta2`, `epsilon` or `gradient` is not a Tensor.
Supported Platforms: Supported Platforms:
``Ascend`` ``GPU`` ``Ascend`` ``GPU`` ``CPU``
Examples: Examples:
>>> import numpy as np >>> import numpy as np
@ -6999,7 +6999,7 @@ class CTCLoss(PrimitiveWithInfer):
TypeError: If dtype of `labels_values` or `sequence_length` is not int32. TypeError: If dtype of `labels_values` or `sequence_length` is not int32.
Supported Platforms: Supported Platforms:
``Ascend`` ``GPU`` ``Ascend`` ``GPU`` ``CPU``
Examples: Examples:
>>> np.random.seed(0) >>> np.random.seed(0)