[Fluid Clean] remove unfold, deformable_roi_pooling, shard_index, hard_swish, mish, uniform_random, unbind (#48451)

Author: heyanru01

python/paddle/distribution/uniform.py

@@ -23,7 +23,7 @@
     _non_static_mode,
     in_dygraph_mode,
 )
-from paddle.fluid.layers import nn, tensor
+from paddle.fluid.layers import tensor
 from paddle.tensor import random
 
 
@@ -187,7 +187,7 @@ def sample(self, shape, seed=0):
             return output
         else:
             output_shape = shape + batch_shape
-            output = nn.uniform_random(
+            output = paddle.uniform(
                 output_shape, dtype=self.dtype, min=0.0, max=1.0, seed=seed
             ) * (
                 tensor.zeros(output_shape, dtype=self.dtype)

python/paddle/fluid/layers/nn.py

@@ -1097,7 +1097,6 @@ set_tests_properties(test_bilinear_interp_v2_op PROPERTIES TIMEOUT 120)
 set_tests_properties(test_svd_op PROPERTIES TIMEOUT 80)
 set_tests_properties(test_einsum_op PROPERTIES TIMEOUT 120)
 set_tests_properties(test_qr_op PROPERTIES TIMEOUT 60)
-set_tests_properties(test_deformable_psroi_pooling PROPERTIES TIMEOUT 120)
 set_tests_properties(test_trilinear_interp_v2_op PROPERTIES TIMEOUT 120)
 set_tests_properties(test_imperative_static_runner_mnist PROPERTIES TIMEOUT 120)
 set_tests_properties(test_masked_select_op PROPERTIES TIMEOUT 120)

python/paddle/fluid/tests/unittests/CMakeLists.txt

@@ -102,7 +102,7 @@ class ElementwiseActivationMkldnnFusePassTest_Add_HardSwish(
 ):
     def set_params(self):
         self.operand = paddle.add
-        self.act = fluid.layers.hard_swish
+        self.act = paddle.nn.functional.hardswish
 
 
 class ElementwiseActivationMkldnnFusePassTest_Add_SQRT(
@@ -202,7 +202,7 @@ class ElementwiseActivationMkldnnFusePassTest_Sub_HardSwish(
 ):
     def set_params(self):
         self.operand = paddle.subtract
-        self.act = fluid.layers.hard_swish
+        self.act = paddle.nn.functional.hardswish
 
 
 class ElementwiseActivationMkldnnFusePassTest_Sub_ABS(
@@ -294,7 +294,7 @@ class ElementwiseActivationMkldnnFusePassTest_Mul_HardSwish(
 ):
     def set_params(self):
         self.operand = paddle.multiply
-        self.act = fluid.layers.hard_swish
+        self.act = paddle.nn.functional.hardswish
 
 
 class ElementwiseActivationMkldnnFusePassTest_Mul_SQRT(

python/paddle/fluid/tests/unittests/ir/inference/test_mkldnn_elt_act_fuse_pass.py

@@ -88,7 +88,7 @@ def append_act(self, x):
 
 class TensorRTSubgraphPassHardSwishTest(TensorRTSubgraphPassActivationTest):
     def append_act(self, x):
-        return fluid.layers.hard_swish(x)
+        return paddle.nn.functional.hardswish(x)
 
 
 class TensorRTSubgraphPassHardSigmoidTest(TensorRTSubgraphPassActivationTest):
@@ -100,7 +100,7 @@ class TensorRTSubgraphPassHardSwishPluginTest(
     TensorRTSubgraphPassActivationTest
 ):
     def append_act(self, x):
-        return fluid.layers.hard_swish(x, threshold=4.0, scale=8.0)
+        return paddle.nn.functional.hardswish(x)
 
 
 class TensorRTSubgraphPassClipTest(TensorRTSubgraphPassActivationTest):
@@ -166,7 +166,7 @@ def setUpTensorRTParam(self):
         )
 
     def append_act(self, x):
-        return fluid.layers.mish(x)
+        return paddle.nn.functional.mish(x)
 
 
 class TensorRTSubgraphPassMishFp16SerializeTest(
@@ -179,7 +179,7 @@ def setUpTensorRTParam(self):
         )
 
     def append_act(self, x):
-        return fluid.layers.mish(x)
+        return paddle.nn.functional.mish(x)
 
 
 class TensorRTSubgraphPassDynamicMishFp16SerializeTest(
@@ -200,7 +200,7 @@ def setUpTensorRTParam(self):
         )
 
     def append_act(self, x):
-        return fluid.layers.mish(x)
+        return paddle.nn.functional.mish(x)
 
 
 class TensorRTSubgraphPassPreluAllTest(TensorRTSubgraphPassActivationTest):

python/paddle/fluid/tests/unittests/ir/inference/test_trt_activation_pass.py

@@ -2073,15 +2073,15 @@ def test_dygraph_api(self):
     def test_fluid_api(self):
         with fluid.program_guard(fluid.Program()):
             x = fluid.data('X', self.x_np.shape, self.x_np.dtype)
-            out = fluid.layers.hard_swish(x)
+            out = paddle.nn.functional.hardswish(x)
             exe = fluid.Executor(self.place)
             res = exe.run(feed={'X': self.x_np}, fetch_list=[out])
         out_ref = ref_hardswish(self.x_np)
         np.testing.assert_allclose(out_ref, res[0], rtol=1e-05)
 
         paddle.disable_static(self.place)
         x = paddle.to_tensor(self.x_np)
-        out = paddle.fluid.layers.hard_swish(x)
+        out = paddle.nn.functional.hardswish(x)
         np.testing.assert_allclose(out_ref, out.numpy(), rtol=1e-05)
         paddle.enable_static()
 
@@ -3414,7 +3414,7 @@ def ref_mish(x, threshold=20.0):
 class TestMish(TestActivation):
     def setUp(self):
         self.op_type = "mish"
-        self.python_api = paddle.fluid.layers.nn.mish
+        self.python_api = paddle.nn.functional.mish
         self.init_dtype()
         self.init_shape()
 
@@ -3480,7 +3480,7 @@ def test_fluid_api(self):
         paddle.enable_static()
         with fluid.program_guard(fluid.Program()):
             x = fluid.data('X', self.x_np.shape, self.x_np.dtype)
-            out = fluid.layers.mish(x)
+            out = paddle.nn.functional.mish(x)
             exe = fluid.Executor(self.place)
             res = exe.run(feed={'X': self.x_np}, fetch_list=[out])
         out_ref = ref_mish(self.x_np)

python/paddle/fluid/tests/unittests/test_activation_op.py

@@ -41,31 +41,19 @@ def test_gen_dropout_dygraph(self):
         gen.manual_seed(111111111)
         st = paddle.get_cuda_rng_state()
 
-        x = fluid.layers.uniform_random(
-            [2, 10], dtype="float32", min=0.0, max=1.0
-        )
-        x_again = fluid.layers.uniform_random(
-            [2, 10], dtype="float32", min=0.0, max=1.0
-        )
-        x_third = fluid.layers.uniform_random(
-            [2, 10], dtype="float32", min=0.0, max=1.0
-        )
+        x = paddle.uniform([2, 10], dtype="float32", min=0.0, max=1.0)
+        x_again = paddle.uniform([2, 10], dtype="float32", min=0.0, max=1.0)
+        x_third = paddle.uniform([2, 10], dtype="float32", min=0.0, max=1.0)
         print("x: {}".format(x.numpy()))
         print("x_again: {}".format(x_again.numpy()))
         x = x + x_again + x_third
         y = fluid.layers.dropout(x, 0.5)
 
         paddle.set_cuda_rng_state(st)
 
-        x1 = fluid.layers.uniform_random(
-            [2, 10], dtype="float32", min=0.0, max=1.0
-        )
-        x1_again = fluid.layers.uniform_random(
-            [2, 10], dtype="float32", min=0.0, max=1.0
-        )
-        x1_third = fluid.layers.uniform_random(
-            [2, 10], dtype="float32", min=0.0, max=1.0
-        )
+        x1 = paddle.uniform([2, 10], dtype="float32", min=0.0, max=1.0)
+        x1_again = paddle.uniform([2, 10], dtype="float32", min=0.0, max=1.0)
+        x1_third = paddle.uniform([2, 10], dtype="float32", min=0.0, max=1.0)
         x1 = x1 + x1_again + x1_third
         y1 = fluid.layers.dropout(x1, 0.5)
         y_np = y.numpy()
@@ -128,7 +116,7 @@ def test_gen_TruncatedNormal_initializer(self):
         with fluid.program_guard(train_program, startup_program):
             # example 1:
             # attr shape is a list which doesn't contain tensor Variable.
-            x = fluid.layers.uniform_random(shape=[2, 10])
+            x = paddle.uniform(shape=[2, 10])
             result_1 = fluid.layers.fc(
                 input=x,
                 size=10,