[Cherry-Pick]Cherry pick PR41200, PR41474, PR41382 (#41509)

* Use `self`as a parameter of _hash_with_id function to avoid error caused by hash_id reuse (#41200)

* Add fill_constant_batch_size YAML and UT (#41474)

* Switch some dy2st UT to eager mode (#41382)

* Sitch some dy2st UT to eager mode

* Fix test_lstm and remove test_transformer

* Run test_resnet_v2 in old dy mode

python/paddle/fluid/dygraph/varbase_patch_methods.py

@@ -99,7 +99,7 @@ def monkey_patch_varbase():
 
         # Note: getattr(self, attr, None) will call x.grad=x.gradient(), but gradient() only available in dygraph.
         # It will fail. So, for propery that different between dynamic and static graph, should not getattr(self, attr, None).
-        attr_not_need_keys = ['grad', 'T']
+        attr_not_need_keys = ['grad', 'T', 'place', '_place_str']
         if isinstance(self, (ParamBase, EagerParamBase)):
             attr_kwargs = self.__dict__.copy()
         else:

python/paddle/fluid/layers/tensor.py

@@ -846,6 +846,18 @@ def fill_constant_batch_size_like(input,
                     input=like, shape=[1], value=0, dtype='int64') #like=[[10, 10]] data=[0]
 
     """
+    if in_dygraph_mode():
+        if not isinstance(dtype, core.VarDesc.VarType):
+            dtype = convert_np_dtype_to_dtype_(dtype)
+
+        place = _current_expected_place()
+        if force_cpu:
+            place = core.CPUPlace()
+        out = _C_ops.final_state_full_batch_size_like(
+            input, shape, dtype, value, input_dim_idx, output_dim_idx, place)
+        out.stop_gradient = True
+        return out
+
     helper = LayerHelper("fill_constant_batch_size_like", **locals())
     out = helper.create_variable_for_type_inference(dtype=dtype)
     attrs = {

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

@@ -596,6 +596,13 @@ foreach(TEST_OP ${TEST_OPS_WITH_GC})
   py_test_modules(${TEST_OP} MODULES ${TEST_OP} ENVS ${GC_ENVS})
 endforeach()
 
+# Switch some dy2st UT to eager mode
+set(TEST_EAGER_OPS test_jit_save_load test_translated_layer)
+foreach(TEST_OP ${TEST_EAGER_OPS})
+  list(REMOVE_ITEM TEST_OPS ${TEST_OP})
+  py_test_modules(${TEST_OP} MODULES ${TEST_OP} ENVS FLAGS_enable_eager_mode=1)
+endforeach()
+
 if ((NOT WITH_GPU) AND (NOT WITH_XPU) AND NOT (WITH_ASCEND OR WITH_ASCEND_CL))
     list(REMOVE_ITEM TEST_OPS "test_fleet_graph_execution_meta_optimizer")
     list(REMOVE_ITEM TEST_OPS "test_gen_nccl_id_op")

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

@@ -6,7 +6,7 @@ set(DY2ST_EAGER_TEST_ENVS ${GC_ENVS} FLAGS_enable_eager_mode=1)
 set(TEST_EAGER_OPS test_bmn test_break_continue test_ifelse test_loop test_mnist_amp 
     test_mnist_pure_fp16 test_mobile_net test_program_translator test_ptb_lm test_reinforcement_learning 
     test_resnet test_resnet_amp test_resnet_pure_fp16 test_se_resnet test_sentiment test_seq2seq 
-    test_tsm test_word2vec test_yolov3)
+    test_tsm test_word2vec test_yolov3 test_bert test_cycle_gan test_lstm test_simnet)
 list(REMOVE_ITEM TEST_OPS test_lac)
 # NOTE(Aurelius84): In case of Windows CI, if open ON_INFER, RWLOCK of Scope will
 # be removed and will cause some random failed in multi-thread.

python/paddle/fluid/tests/unittests/dygraph_to_static/test_resnet_v2.py

@@ -14,6 +14,8 @@
 
 from __future__ import print_function
 
+import os
+os.environ["FLAGS_enable_eager_mode"] = "0"
 import math
 import time
 import unittest

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

+#   Copyright (c) 2019 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 paddle
+import paddle.fluid.core as core
+from paddle.static import program_guard, Program
+import paddle.compat as cpt
+import unittest
+import numpy as np
+from op_test import OpTest
+from paddle.fluid.framework import convert_np_dtype_to_dtype_
+
+paddle.enable_static()
+
+
+def fill_constant_batch_size_like(input,
+                                  shape,
+                                  value,
+                                  data_type,
+                                  input_dim_idx=0,
+                                  output_dim_idx=0,
+                                  force_cpu=False):
+    return paddle.fluid.layers.fill_constant_batch_size_like(
+        input, shape, data_type, value, input_dim_idx, output_dim_idx,
+        force_cpu)
+
+
+class TestFillConstatnBatchSizeLike1(OpTest):
+    # test basic
+    def setUp(self):
+        self.op_type = "fill_constant_batch_size_like"
+        self.python_api = fill_constant_batch_size_like
+        self.init_data()
+
+        input = np.zeros(self.shape)
+        out = np.full_like(input, self.value, self.dtype)
+
+        self.inputs = {'Input': input}
+        self.outputs = {'Out': out}
+        self.attrs = {
+            'shape': self.shape,
+            'dtype': convert_np_dtype_to_dtype_(self.dtype),
+            'value': self.value,
+            'input_dim_idx': self.input_dim_idx,
+            'output_dim_idx': self.output_dim_idx,
+            'force_cpu': self.force_cpu
+        }
+
+    def init_data(self):
+        self.shape = [10, 10]
+        self.dtype = np.float32
+        self.value = 100
+        self.input_dim_idx = 0
+        self.output_dim_idx = 0
+        self.force_cpu = False
+
+    def test_check_output(self):
+        self.check_output(check_eager=True)
+
+
+if __name__ == "__main__":
+    unittest.main()

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

@@ -99,7 +99,7 @@ class RunProgramOpTest(unittest.TestCase):
     def prepare_attrs(self):
         return ('global_block', self.program_desc.block(0), 'start_op_index', 0,
                 'end_op_index', self.fwd_op_num, 'program_id',
-                _hash_with_id(self.program_desc))
+                _hash_with_id(self.program_desc, self))
 
     def get_param_grad_names(self):
         grad_names = []

python/paddle/utils/code_gen/api.yaml

@@ -687,6 +687,18 @@
     data_type : dtype
     backend : place
 
+- api : full_batch_size_like
+  args : (Tensor input, int[] shape, DataType dtype, Scalar value, int input_dim_idx, int output_dim_idx, Place place=CPUPlace())
+  output: Tensor
+  infer_meta :
+    func : FullBatchSizeLikeInferMeta
+    param : [input, shape, value, dtype, input_dim_idx, output_dim_idx]
+  kernel :
+    func : full_batch_size_like
+    param : [input, shape, value, dtype, input_dim_idx, output_dim_idx]
+    data_type : dtype
+    backend : place
+
 - api : full_like
   args : (Tensor x, Scalar value, DataType dtype = DataType::UNDEFINED, Place place = {})
   output: Tensor