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!38512 [MSLITE] Fix documents of uniform. 

Merge pull request !38512 from wangshaocong/uniform_ops
This commit is contained in:
i-robot 2022-08-24 09:09:52 +00:00 committed by Gitee
parent 6806bf42cd 492b0d1b92
commit 2b5bce1b42
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GPG Key ID: 173E9B9CA92EEF8F
7 changed files with 21 additions and 19 deletions
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12
mindspore/core/ops/uniform_int.cc
View File

@ -62,23 +62,25 @@ abstract::AbstractBasePtr UniformIntInfer(const abstract::AnalysisEnginePtr &, c
abstract::ShapePtr minval_shape = minval->shape();
MS_EXCEPTION_IF_NULL(minval_shape);
if (minval_shape->IsDimUnknown() || minval_shape->shape().size() != 0) {
MS_LOG(EXCEPTION) << "The min value should be a scalar tensor, while the shape is: " << minval_shape->ToString();
MS_EXCEPTION(ValueError) << "The min value should be a scalar tensor, while the shape is: "
<< minval_shape->ToString();
}
abstract::AbstractTensorPtr maxval = abstract::CheckArg<abstract::AbstractTensor>(op_name, input_args, 2);
(void)CheckAndConvertUtils::CheckTensorTypeValid("maxval", maxval->BuildType(), {kInt32}, op_name);
abstract::ShapePtr maxval_shape = maxval->shape();
MS_EXCEPTION_IF_NULL(maxval_shape);
if (maxval_shape->IsDimUnknown() || maxval_shape->shape().size() != 0) {
MS_LOG(EXCEPTION) << "The max value should be a scalar tensor, while the shape is: " << minval_shape->ToString();
MS_EXCEPTION(ValueError) << "The max value should be a scalar tensor, while the shape is: "
<< minval_shape->ToString();
}
ShapeVector shape;
abstract::ShapePtr output_shape;
auto shape_value = input_args[0]->BuildValue();
if (!shape_value->isa<AnyValue>() && !shape_value->isa<None>()) {
shape = shape_value->isa<ValueTuple>()
? CheckAndConvertUtils::CheckTupleInt("input[shape]", shape_value, op_name)
: CheckAndConvertUtils::CheckTensorIntValue("input[shape]", shape_value, op_name);
shape = shape_value->isa<tensor::Tensor>()
? CheckAndConvertUtils::CheckTensorIntValue("input[shape]", shape_value, op_name)
: CheckAndConvertUtils::CheckTupleInt("input[shape]", shape_value, op_name);
output_shape = std::make_shared<abstract::Shape>(shape);
} else {
shape = {-2}; // unknown dimension.

6
mindspore/core/ops/uniform_int.h
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@ -14,8 +14,8 @@
* limitations under the License.
*/
#ifndef MINDSPORE_CORE_OPS_RANDOM_UNIFORM_INT_H_
#define MINDSPORE_CORE_OPS_RANDOM_UNIFORM_INT_H_
#ifndef MINDSPORE_CORE_OPS_UNIFORM_INT_H_
#define MINDSPORE_CORE_OPS_UNIFORM_INT_H_
#include <map>
#include <vector>
#include <string>
@ -56,4 +56,4 @@ abstract::AbstractBasePtr UniformIntInfer(const abstract::AnalysisEnginePtr &, c
} // namespace ops
} // namespace mindspore
#endif // MINDSPORE_CORE_OPS_RANDOM_UNIFORM_INT_H_
#endif // MINDSPORE_CORE_OPS_UNIFORM_INT_H_

6
mindspore/core/ops/uniform_real.cc
View File

@ -61,9 +61,9 @@ abstract::AbstractBasePtr UniformRealInfer(const abstract::AnalysisEnginePtr &,
abstract::ShapePtr output_shape;
auto shape_value = input_args[0]->BuildValue();
if (!shape_value->isa<AnyValue>() && !shape_value->isa<None>()) {
shape = shape_value->isa<ValueTuple>()
? CheckAndConvertUtils::CheckTupleInt("input[shape]", shape_value, op_name)
: CheckAndConvertUtils::CheckTensorIntValue("input[shape]", shape_value, op_name);
shape = shape_value->isa<tensor::Tensor>()
? CheckAndConvertUtils::CheckTensorIntValue("input[shape]", shape_value, op_name)
: CheckAndConvertUtils::CheckTupleInt("input[shape]", shape_value, op_name);
output_shape = std::make_shared<abstract::Shape>(shape);
} else {
shape = {-2}; // unknown dimension.

6
mindspore/core/ops/uniform_real.h
View File

@ -14,8 +14,8 @@
* limitations under the License.
*/
#ifndef MINDSPORE_CORE_OPS_RANDOM_UNIFORM_REAL_H_
#define MINDSPORE_CORE_OPS_RANDOM_UNIFORM_REAL_H_
#ifndef MINDSPORE_CORE_OPS_UNIFORM_REAL_H_
#define MINDSPORE_CORE_OPS_UNIFORM_REAL_H_
#include <map>
#include <vector>
#include <string>
@ -55,4 +55,4 @@ abstract::AbstractBasePtr UniformRealInfer(const abstract::AnalysisEnginePtr &,
} // namespace ops
} // namespace mindspore
#endif // MINDSPORE_CORE_OPS_RANDOM_UNIFORM_REAL_H_
#endif // MINDSPORE_CORE_OPS_UNIFORM_REAL_H_

2
mindspore/python/mindspore/nn/probability/distribution/uniform.py
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@ -51,7 +51,7 @@ class Uniform(Distribution):
TypeError: When the input `dtype` is not a subclass of float.
Supported Platforms:
``Ascend`` ``GPU``
``Ascend`` ``GPU`` ``CPU``
Examples:
>>> import mindspore

2
mindspore/python/mindspore/ops/composite/random_ops.py
View File

@ -174,7 +174,7 @@ def uniform(shape, minval, maxval, seed=None, dtype=mstype.float32):
TypeError: If 'dtype' is neither int32 nor float32.
Supported Platforms:
``Ascend`` ``GPU``
``Ascend`` ``GPU`` ``CPU``
Examples:
>>> from mindspore import Tensor, ops

6
mindspore/python/mindspore/ops/function/random_func.py
View File

@ -200,7 +200,7 @@ def uniform(shape, minval, maxval, seed=None, dtype=mstype.float32):
TypeError: If 'dtype' is neither int32 nor float32.
Supported Platforms:
``Ascend`` ``GPU``
``Ascend`` ``GPU`` ``CPU``
Examples:
>>> from mindspore import Tensor, ops
@ -210,13 +210,13 @@ def uniform(shape, minval, maxval, seed=None, dtype=mstype.float32):
>>> shape = (4, 2)
>>> minval = Tensor(1, mindspore.int32)
>>> maxval = Tensor(2, mindspore.int32)
>>> output = F.uniform(shape, minval, maxval, seed=5, dtype=mindspore.int32)
>>> output = ops.uniform(shape, minval, maxval, seed=5, dtype=mindspore.int32)
>>>
>>> # For continuous uniform distribution, minval and maxval can be multi-dimentional:
>>> shape = (3, 1, 2)
>>> minval = Tensor(np.array([[3, 4], [5, 6]]), mindspore.float32)
>>> maxval = Tensor([8.0, 10.0], mindspore.float32)
>>> output = F.uniform(shape, minval, maxval, seed=5)
>>> output = ops.uniform(shape, minval, maxval, seed=5)
>>> result = output.shape
>>> print(result)
(3, 2, 2)