chore: import upstream snapshot with attribution

python/paddle/nn/quant/functional_layers.py

@@ -0,0 +1,95 @@
+#   Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# 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.
+
+from ...tensor import linalg, manipulation, math
+from ..layer.layers import Layer
+
+__all__ = []
+
+
+class FloatFunctionalLayer(Layer):
+    def __init__(self):
+        super().__init__()
+
+
+class add(FloatFunctionalLayer):
+    def __init__(self):
+        super().__init__()
+
+    def forward(self, x, y, name=None):
+        return math.add(x, y, name=name)
+
+
+class subtract(FloatFunctionalLayer):
+    def __init__(self):
+        super().__init__()
+
+    def forward(self, x, y, name=None):
+        return math.subtract(x, y, name=name)
+
+
+class multiply(FloatFunctionalLayer):
+    def __init__(self):
+        super().__init__()
+
+    def forward(self, x, y, name=None):
+        return math.multiply(x, y, name=name)
+
+
+class divide(FloatFunctionalLayer):
+    def __init__(self):
+        super().__init__()
+
+    def forward(self, x, y, name=None):
+        return math.divide(x, y, name=name)
+
+
+class reshape(FloatFunctionalLayer):
+    def __init__(self):
+        super().__init__()
+
+    def forward(self, x, shape, name=None):
+        return manipulation.reshape(x, shape, name=name)
+
+
+class transpose(FloatFunctionalLayer):
+    def __init__(self):
+        super().__init__()
+
+    def forward(self, x, perm, name=None):
+        return manipulation.transpose(x, perm, name=name)
+
+
+class concat(FloatFunctionalLayer):
+    def __init__(self):
+        super().__init__()
+
+    def forward(self, x, axis=0, name=None):
+        return manipulation.concat(x, axis, name=name)
+
+
+class flatten(FloatFunctionalLayer):
+    def __init__(self):
+        super().__init__()
+
+    def forward(self, x, start_axis=0, stop_axis=-1, name=None):
+        return manipulation.flatten(x, start_axis, stop_axis, name=name)
+
+
+class matmul(FloatFunctionalLayer):
+    def __init__(self):
+        super().__init__()
+
+    def forward(self, x, y, transpose_x=False, transpose_y=False, name=None):
+        return linalg.matmul(x, y, transpose_x, transpose_y, name=name)