!47533 api: ravel

Merge pull request !47533 from 于振华/api_ravel_0104

docs/api/api_python/mindspore.ops.rst

@@ -270,6 +270,7 @@ mindspore.ops
     mindspore.ops.positive
     mindspore.ops.pow
     mindspore.ops.rad2deg
+    mindspore.ops.ravel
     mindspore.ops.real
     mindspore.ops.reciprocal
     mindspore.ops.remainder
@@ -454,6 +455,7 @@ Array操作
     mindspore.ops.flipud
     mindspore.ops.fold
     mindspore.ops.full
+    mindspore.ops.full_like
     mindspore.ops.gather
     mindspore.ops.gather_d
     mindspore.ops.gather_elements

docs/api/api_python/ops/mindspore.ops.func_full_like.rst

@@ -0,0 +1,19 @@
+mindspore.ops.full_like
+=======================
+
+.. py:function:: mindspore.ops.full_like(x, fill_value, *, dtype=None)
+
+    返回一个与输入相同大小的Tensor，填充 `fill_value`。'ops.full_like(x, fill_value)'相当于'ops.full(x.shape, fill_value, dtype=x.dtype)'。
+
+    参数：
+        - **x** (Tensor) - `x` 的shape决定输出Tensor的shape。
+        - **fill_value** (number.Number) - 用来填充输出Tensor的值。
+
+    关键字参数：
+        - **dtype** (mindspore.dtype) - 指定输出Tensor的数据类型。数据类型只支持 `bool_` 和 `number ` ，更多细节详见 :class:`mindspore.dtype` 。默认值：None。
+
+    返回：
+        Tensor。
+
+    异常：
+        - **TypeError** - `x` 不是Tensor。

docs/api/api_python/ops/mindspore.ops.func_ravel.rst

@@ -0,0 +1,15 @@
+mindspore.ops.ravel
+======================
+
+.. py:method:: mindspore.ops.ravel(x)
+
+    返回一个展开的一维Tensor。
+
+    参数：
+        - **x** (Tensor) - 要展开的Tensor。
+
+    返回：
+        一维Tensor，含有与输入相同的元素。
+
+    异常：
+        - **TypeError** - 如果 `x` 不是Tensor。

docs/api/api_python_en/mindspore.ops.rst

@@ -270,6 +270,7 @@ Element-by-Element Operations
     mindspore.ops.positive
     mindspore.ops.pow
     mindspore.ops.rad2deg
+    mindspore.ops.ravel
     mindspore.ops.real
     mindspore.ops.reciprocal
     mindspore.ops.remainder
@@ -454,6 +455,7 @@ Array Operation
     mindspore.ops.flipud
     mindspore.ops.fold
     mindspore.ops.full
+    mindspore.ops.full_like
     mindspore.ops.gather
     mindspore.ops.gather_d
     mindspore.ops.gather_elements

mindspore/python/mindspore/ops/function/__init__.py

@@ -36,6 +36,7 @@ from .array_func import (
     fill,
     fill_,
     full,
+    full_like,
     chunk,
     tile,
     size,
@@ -49,6 +50,7 @@ from .array_func import (
     dyn_shape,
     rank,
     hamming_window,
+    ravel,
     reshape,
     reshape_,
     reverse,

mindspore/python/mindspore/ops/function/array_func.py

@@ -464,6 +464,33 @@ def reverse(x, axis):
     return P.ReverseV2(axis)(x)
 
 
+def ravel(x):
+    """
+    Return a contiguous flattened tensor.
+
+    Args:
+        x (Tensor): A tensor to be flattened.
+
+    Outputs:
+        Tensor, a 1-D tensor, containing the same elements of the input.
+
+    Raises:
+        TypeError: If argument `x` is not Tensor.
+
+    Supported Platforms:
+        ``Ascend`` ``GPU`` ``CPU``
+
+    Examples:
+        >>> x = Tensor(np.array([[0, 1], [2, 1]]).astype(np.float32))
+        >>> output = ops.ravel(x)
+        >>> print(output)
+        [0, 1, 2, 1]
+        >>> print(output.shape)
+        (4,)
+    """
+    return ops.reshape(x, (-1,))
+
+
 def matrix_band_part(x, lower, upper):
     r"""
     Copy a tensor setting everything outside a central band in each innermost matrix to zero.
@@ -713,6 +740,46 @@ def full(size, fill_value, *, dtype=None): # pylint: disable=redefined-outer-nam
     return fill_(dtype, size, fill_value)
 
 
+def full_like(x, fill_value, *, dtype=None):
+    """
+    Returns  a Tensor with the same size as `x` filled with `fill_value`. 'ops.full_like(x, fill_value)' is
+    equivalent to 'ops.full(x.shape, fill_value, dtype=x.dtype)'.
+
+    Args:
+        x (Tensor): The shape of `x` will determine shape of the output Tensor.
+        fill_value (number.Number): Value to fill the returned Tensor.
+
+    Keyword Args:
+        dtype (mindspore.dtype, optional): The specified type of output tensor. The data type only supports
+            `bool_` and `number` , for details, please refer to :class:`mindspore.dtype` . Default: None.
+
+    Returns:
+        Tensor.
+
+    Raises:
+        TypeError: If `x` is not a Tensor.
+
+    Supported Platforms:
+        ``Ascend`` ``GPU`` ``CPU``
+
+    Examples:
+        >>> output = ops.full((2, 2), 1)
+        >>> print(output)
+        [[1. 1.]
+         [1. 1.]]
+        >>> output = ops.full((3, 3), 0)
+        >>> print(output)
+        [[0. 0. 0.]
+         [0. 0. 0.]
+         [0. 0. 0.]]
+    """
+    if not isinstance(x, Tensor):
+        raise TypeError(f"For ops.full_like, the argument 'x' must be tensor, but got {type(x)}")
+    if dtype is None:
+        dtype = x.dtype
+    return full(x.shape, fill_value, dtype=dtype)
+
+
 def chunk(x, chunks, axis=0):
     """
     Splits the Tensor into chunks along the given axis.
@@ -6195,6 +6262,7 @@ __all__ = [
     'hamming_window',
     'chunk',
     'full',
+    'full_like',
     'dyn_shape',
     'rank',
     'range',
@@ -6245,6 +6313,7 @@ __all__ = [
     'masked_select',
     'where',
     'narrow',
+    'ravel',
     'scatter_add',
     'scatter_mul',
     'scatter_max',

tests/st/ops/test_func_full_like.py

@@ -0,0 +1,51 @@
+# Copyright 2023 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+
+import numpy as np
+import pytest
+
+import mindspore as ms
+import mindspore.nn as nn
+import mindspore.ops as ops
+from mindspore import Tensor
+
+
+class Net(nn.Cell):
+    def construct(self, x, fill_value):
+        output = ops.full_like(x, fill_value)
+        return output
+
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_cpu
+@pytest.mark.platform_arm_cpu
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
+@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE])
+def test_full_normal(mode):
+    """
+    Feature: ops.full
+    Description: Verify the result of ops.full
+    Expectation: success
+    """
+    ms.set_context(mode=mode)
+    net = Net()
+    x = Tensor([[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]])
+    fill_value = 11
+    out = net(x, fill_value)
+    expect_out = np.array([[[11, 11, 11, 11], [11, 11, 11, 11], [11, 11, 11, 11]]])
+    assert np.allclose(out.asnumpy(), expect_out)

tests/st/ops/test_func_ravel.py

@@ -0,0 +1,47 @@
+# Copyright 2023 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+import numpy as np
+import pytest
+import mindspore as ms
+import mindspore.nn as nn
+from mindspore import Tensor
+from mindspore import ops
+
+
+class Net(nn.Cell):
+    def construct(self, x):
+        return ops.ravel(x)
+
+
+@pytest.mark.level0
+@pytest.mark.platform_x86_cpu
+@pytest.mark.platform_arm_cpu
+@pytest.mark.platform_x86_gpu_training
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.env_onecard
+@pytest.mark.parametrize('mode', [ms.GRAPH_MODE, ms.PYNATIVE_MODE])
+def test_tensor_ravel(mode):
+    """
+    Feature: ops.ravel
+    Description: Verify the result of ravel
+    Expectation: success
+    """
+    ms.set_context(mode=mode)
+    x = Tensor([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]], ms.int32)
+    net = Net()
+    output = net(x)
+    expect_output = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]
+    assert np.allclose(output.asnumpy(), expect_output)