add squeeze_op_npu and test (#34077)

paddle/fluid/operators/squeeze_op_npu.cc

@@ -12,11 +12,6 @@ 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. */
 
-#ifdef PADDLE_WITH_ASCEND_CL
-#include <memory>
-#include <string>
-
-#include "paddle/fluid/operators/npu_op_runner.h"
 #include "paddle/fluid/operators/squeeze_op.h"
 
 namespace ops = paddle::operators;
@@ -40,4 +35,21 @@ REGISTER_OP_NPU_KERNEL(
     ops::SqueezeKernel<plat::NPUDeviceContext, uint8_t>,
     ops::SqueezeKernel<plat::NPUDeviceContext, int8_t>,
     ops::SqueezeKernel<plat::NPUDeviceContext, int64_t>);
-#endif
+REGISTER_OP_NPU_KERNEL(
+    squeeze_grad, ops::SqueezeGradKernel<plat::NPUDeviceContext, float>,
+    ops::SqueezeGradKernel<plat::NPUDeviceContext, double>,
+    ops::SqueezeGradKernel<plat::NPUDeviceContext, plat::float16>,
+    ops::SqueezeGradKernel<plat::NPUDeviceContext, bool>,
+    ops::SqueezeGradKernel<plat::NPUDeviceContext, int>,
+    ops::SqueezeGradKernel<plat::NPUDeviceContext, uint8_t>,
+    ops::SqueezeGradKernel<plat::NPUDeviceContext, int8_t>,
+    ops::SqueezeGradKernel<plat::NPUDeviceContext, int64_t>);
+REGISTER_OP_NPU_KERNEL(
+    squeeze2_grad, ops::Squeeze2GradKernel<plat::NPUDeviceContext, float>,
+    ops::Squeeze2GradKernel<plat::NPUDeviceContext, double>,
+    ops::Squeeze2GradKernel<plat::NPUDeviceContext, plat::float16>,
+    ops::Squeeze2GradKernel<plat::NPUDeviceContext, bool>,
+    ops::Squeeze2GradKernel<plat::NPUDeviceContext, int>,
+    ops::Squeeze2GradKernel<plat::NPUDeviceContext, uint8_t>,
+    ops::Squeeze2GradKernel<plat::NPUDeviceContext, int8_t>,
+    ops::Squeeze2GradKernel<plat::NPUDeviceContext, int64_t>);

python/paddle/fluid/tests/unittests/npu/test_squeeze_op_npu.py

+#   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 __future__ import print_function
+
+import numpy as np
+import unittest
+import sys
+sys.path.append("..")
+from op_test import OpTest
+import paddle
+import paddle.fluid as fluid
+import paddle.fluid.core as core
+from paddle.fluid import Program, program_guard
+
+paddle.enable_static()
+
+
+# Correct: General.
+@unittest.skipIf(not paddle.is_compiled_with_npu(),
+                 "core is not compiled with NPU")
+class TestSqueezeOp(OpTest):
+    def setUp(self):
+        self.set_npu()
+        self.op_type = "squeeze"
+        self.init_test_case()
+        self.inputs = {"X": np.random.random(self.ori_shape).astype("float32")}
+        self.init_attrs()
+        self.outputs = {"Out": self.inputs["X"].reshape(self.new_shape), }
+
+    def set_npu(self):
+        self.__class__.use_npu = True
+
+    def test_check_output(self):
+        self.check_output_with_place(paddle.NPUPlace(0))
+
+    def test_check_grad(self):
+        self.check_grad_with_place(paddle.NPUPlace(0), ["X"], "Out")
+
+    def init_test_case(self):
+        self.ori_shape = (1, 3, 1, 40)
+        self.axes = (0, 2)
+        self.new_shape = (3, 40)
+
+    def init_attrs(self):
+        self.attrs = {"axes": self.axes}
+
+
+# Correct: There is mins axis.
+@unittest.skipIf(not paddle.is_compiled_with_npu(),
+                 "core is not compiled with NPU")
+class TestSqueezeOp1(TestSqueezeOp):
+    def init_test_case(self):
+        self.ori_shape = (1, 3, 1, 40)
+        self.axes = (0, -2)
+        self.new_shape = (3, 40)
+
+
+# Correct: No axes input.
+@unittest.skipIf(not paddle.is_compiled_with_npu(),
+                 "core is not compiled with NPU")
+class TestSqueezeOp2(TestSqueezeOp):
+    def init_test_case(self):
+        self.ori_shape = (1, 20, 1, 5)
+        self.axes = ()
+        self.new_shape = (20, 5)
+
+
+# Correct: Just part of axes be squeezed. 
+@unittest.skipIf(not paddle.is_compiled_with_npu(),
+                 "core is not compiled with NPU")
+class TestSqueezeOp3(TestSqueezeOp):
+    def init_test_case(self):
+        self.ori_shape = (6, 1, 5, 1, 4, 1)
+        self.axes = (1, -1)
+        self.new_shape = (6, 5, 1, 4)
+
+
+# Correct: The demension of axis is not of size 1 remains unchanged.
+@unittest.skipIf(not paddle.is_compiled_with_npu(),
+                 "core is not compiled with NPU")
+class TestSqueezeOp4(TestSqueezeOp):
+    def init_test_case(self):
+        self.ori_shape = (6, 1, 5, 1, 4, 1)
+        self.axes = (1, 2)
+        self.new_shape = (6, 5, 1, 4, 1)
+
+
+class TestSqueezeOpError(unittest.TestCase):
+    def test_errors(self):
+        paddle.enable_static()
+        with program_guard(Program(), Program()):
+            # The input type of softmax_op must be Variable.
+            x1 = fluid.create_lod_tensor(
+                np.array([[-1]]), [[1]], paddle.NPUPlace(0))
+            self.assertRaises(TypeError, paddle.squeeze, x1)
+            # The input axes of squeeze must be list.
+            x2 = paddle.static.data(name='x2', shape=[4], dtype="int32")
+            self.assertRaises(TypeError, paddle.squeeze, x2, axes=0)
+            # The input dtype of squeeze not support float16.
+            x3 = paddle.static.data(name='x3', shape=[4], dtype="float16")
+            self.assertRaises(TypeError, paddle.squeeze, x3, axes=0)
+
+
+class API_TestSqueeze(unittest.TestCase):
+    def setUp(self):
+        self.executed_api()
+
+    def executed_api(self):
+        self.squeeze = paddle.squeeze
+
+    def test_out(self):
+        paddle.enable_static()
+        with paddle.static.program_guard(paddle.static.Program(),
+                                         paddle.static.Program()):
+            data1 = paddle.static.data(
+                'data1', shape=[-1, 1, 10], dtype='float64')
+            result_squeeze = self.squeeze(data1, axis=[1])
+            place = paddle.NPUPlace(0)
+            exe = paddle.static.Executor(place)
+            input1 = np.random.random([5, 1, 10]).astype('float64')
+            result, = exe.run(feed={"data1": input1},
+                              fetch_list=[result_squeeze])
+            expected_result = np.squeeze(input1, axis=1)
+            self.assertTrue(np.allclose(expected_result, result))
+
+
+class API_TestStaticSqueeze_(API_TestSqueeze):
+    def executed_api(self):
+        self.squeeze = paddle.squeeze_
+
+
+class API_TestDygraphSqueeze(unittest.TestCase):
+    def setUp(self):
+        self.executed_api()
+
+    def executed_api(self):
+        self.squeeze = paddle.squeeze
+
+    def test_out(self):
+        paddle.disable_static()
+        with fluid.dygraph.guard(paddle.NPUPlace(0)):
+            input_1 = np.random.random([5, 1, 10]).astype("int32")
+            input = paddle.to_tensor(input_1)
+            output = self.squeeze(input, axis=[1])
+            out_np = output.numpy()
+            expected_out = np.squeeze(input_1, axis=1)
+            self.assertTrue(np.allclose(expected_out, out_np))
+
+    def test_out_int8(self):
+        paddle.disable_static()
+        with fluid.dygraph.guard(paddle.NPUPlace(0)):
+            input_1 = np.random.random([5, 1, 10]).astype("int8")
+            input = paddle.to_tensor(input_1)
+            output = self.squeeze(input, axis=[1])
+            out_np = output.numpy()
+            expected_out = np.squeeze(input_1, axis=1)
+            self.assertTrue(np.allclose(expected_out, out_np))
+
+    def test_out_uint8(self):
+        paddle.disable_static()
+        with fluid.dygraph.guard(paddle.NPUPlace(0)):
+            input_1 = np.random.random([5, 1, 10]).astype("uint8")
+            input = paddle.to_tensor(input_1)
+            output = self.squeeze(input, axis=[1])
+            out_np = output.numpy()
+            expected_out = np.squeeze(input_1, axis=1)
+            self.assertTrue(np.allclose(expected_out, out_np))
+
+    def test_axis_not_list(self):
+        paddle.disable_static()
+        with fluid.dygraph.guard(paddle.NPUPlace(0)):
+            input_1 = np.random.random([5, 1, 10]).astype("int32")
+            input = paddle.to_tensor(input_1)
+            output = self.squeeze(input, axis=1)
+            out_np = output.numpy()
+            expected_out = np.squeeze(input_1, axis=1)
+            self.assertTrue(np.allclose(expected_out, out_np))
+
+    def test_dimension_not_1(self):
+        paddle.disable_static()
+        with fluid.dygraph.guard(paddle.NPUPlace(0)):
+            input_1 = np.random.random([5, 1, 10]).astype("int32")
+            input = paddle.to_tensor(input_1)
+            output = self.squeeze(input, axis=(1, 0))
+            out_np = output.numpy()
+            expected_out = np.squeeze(input_1, axis=1)
+            self.assertTrue(np.allclose(expected_out, out_np))
+
+
+class API_TestDygraphSqueezeInplace(API_TestDygraphSqueeze):
+    def executed_api(self):
+        self.squeeze = paddle.squeeze_
+
+
+# Correct: General.
+class TestSqueeze2Op(OpTest):
+    def setUp(self):
+        self.set_npu()
+        self.op_type = "squeeze2"
+        self.init_test_case()
+        self.inputs = {"X": np.random.random(self.ori_shape).astype("float32")}
+        self.init_attrs()
+        self.outputs = {
+            "Out": self.inputs["X"].reshape(self.new_shape),
+            "XShape": np.random.random(self.ori_shape).astype("float32")
+        }
+
+    def set_npu(self):
+        self.__class__.use_npu = True
+
+    def test_check_output(self):
+        self.check_output_with_place(
+            paddle.NPUPlace(0), no_check_set=['XShape'])
+
+    def test_check_grad(self):
+        self.check_grad_with_place(paddle.NPUPlace(0), ["X"], "Out")
+
+    def init_test_case(self):
+        self.ori_shape = (1, 3, 1, 40)
+        self.axes = (0, 2)
+        self.new_shape = (3, 40)
+
+    def init_attrs(self):
+        self.attrs = {"axes": self.axes}
+
+
+# Correct: There is mins axis.
+class TestSqueeze2Op1(TestSqueeze2Op):
+    def init_test_case(self):
+        self.ori_shape = (1, 20, 1, 5)
+        self.axes = (0, -2)
+        self.new_shape = (20, 5)
+
+
+# Correct: No axes input.
+class TestSqueeze2Op2(TestSqueeze2Op):
+    def init_test_case(self):
+        self.ori_shape = (1, 20, 1, 5)
+        self.axes = ()
+        self.new_shape = (20, 5)
+
+
+# Correct: Just part of axes be squeezed. 
+class TestSqueeze2Op3(TestSqueeze2Op):
+    def init_test_case(self):
+        self.ori_shape = (6, 1, 5, 1, 4, 1)
+        self.axes = (1, -1)
+        self.new_shape = (6, 5, 1, 4)
+
+
+if __name__ == "__main__":
+    unittest.main()