wehub-resource-sync
96 lines
2.5 KiB
Python
96 lines
2.5 KiB
Python
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from ...tensor import linalg, manipulation, math
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from ..layer.layers import Layer
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__all__ = []
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class FloatFunctionalLayer(Layer):
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def __init__(self):
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super().__init__()
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class add(FloatFunctionalLayer):
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def __init__(self):
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super().__init__()
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def forward(self, x, y, name=None):
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return math.add(x, y, name=name)
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class subtract(FloatFunctionalLayer):
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def __init__(self):
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super().__init__()
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def forward(self, x, y, name=None):
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return math.subtract(x, y, name=name)
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class multiply(FloatFunctionalLayer):
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def __init__(self):
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super().__init__()
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def forward(self, x, y, name=None):
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return math.multiply(x, y, name=name)
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class divide(FloatFunctionalLayer):
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def __init__(self):
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super().__init__()
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def forward(self, x, y, name=None):
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return math.divide(x, y, name=name)
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class reshape(FloatFunctionalLayer):
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def __init__(self):
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super().__init__()
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def forward(self, x, shape, name=None):
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return manipulation.reshape(x, shape, name=name)
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class transpose(FloatFunctionalLayer):
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def __init__(self):
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super().__init__()
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def forward(self, x, perm, name=None):
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return manipulation.transpose(x, perm, name=name)
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class concat(FloatFunctionalLayer):
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def __init__(self):
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super().__init__()
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def forward(self, x, axis=0, name=None):
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return manipulation.concat(x, axis, name=name)
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class flatten(FloatFunctionalLayer):
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def __init__(self):
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super().__init__()
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def forward(self, x, start_axis=0, stop_axis=-1, name=None):
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return manipulation.flatten(x, start_axis, stop_axis, name=name)
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class matmul(FloatFunctionalLayer):
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def __init__(self):
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super().__init__()
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def forward(self, x, y, transpose_x=False, transpose_y=False, name=None):
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return linalg.matmul(x, y, transpose_x, transpose_y, name=name)
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