Merge some test bug (#40543)

* switch eager mode and change it

* set default is eager

* set default is eager

* fix error; test=develop

* fix some error; test=develop

* update

* upd

* update code; test=develop

* update

* fix some bug; test=develop

* fix bug; test=develop

* fix bug; test=develop

* fix bug; test=develop

* fix error; test=develop

* format; test=develop
Co-authored-by: NJiabinYang <360788950@qq.com>

paddle/fluid/eager/auto_code_generator/eager_generator.cc

@@ -2032,7 +2032,15 @@ static std::string GenerateSingleOpBase(
   const char* ATTRS_TEMPLATE = "  auto& %s = this->attr_map_;\n";
   std::string grad_attrs_str =
       paddle::string::Sprintf(ATTRS_TEMPLATE, attrs_name);
-
+  if (fwd_op_type == "cast") {
+    // swtich in out dtype
+    const char* CAST_GRAD =
+        "  auto temp_type = %s[\"in_dtype\"];\n"
+        "  %s[\"in_dtype\"] = %s[\"out_dtype\"];\n"
+        "  %s[\"out_dtype\"] = temp_type;\n";
+    grad_attrs_str += paddle::string::Sprintf(CAST_GRAD, attrs_name, attrs_name,
+                                              attrs_name, attrs_name);
+  }
   // Handle dynamic grad attributes
   grad_attrs_str += HandleDynamicGradAttributes(fwd_op_type, attrs_name);
   generated_grad_function_body += grad_attrs_str;

paddle/fluid/eager/grad_tensor_holder.cc

@@ -93,7 +93,7 @@ void GradTensorHolder::add(size_t slot_id, size_t rank,
     // Create new tensor->impl and fill it with 1.0
     if (t.defined()) {
       // Fill 1.0
-      buffer_[slot_id][rank] = paddle::experimental::ones_like(t);
+      buffer_[slot_id][rank] = paddle::experimental::ones_like(t, t.dtype());
     }
   }
 }

paddle/fluid/pybind/eager_utils.cc

@@ -62,6 +62,8 @@ int TensorDtype2NumpyDtype(phi::DataType dtype) {
       return pybind11::detail::npy_api::NPY_INT32_;
     case phi::DataType::INT64:
       return pybind11::detail::npy_api::NPY_INT64_;
+    case phi::DataType::BFLOAT16:
+      return pybind11::detail::NPY_UINT16_;
     case phi::DataType::FLOAT16:
       return pybind11::detail::NPY_FLOAT16_;
     case phi::DataType::BFLOAT16:

python/paddle/fluid/dygraph/base.py

@@ -612,7 +612,7 @@ def grad(outputs,
 
     if no_grad_vars is None:
         no_grad_vars = []
-    elif isinstance(no_grad_vars, core.VarBase):
+    elif isinstance(no_grad_vars, (core.VarBase, core.eager.Tensor)):
         no_grad_vars = [no_grad_vars]
     elif isinstance(no_grad_vars, core.eager.Tensor):
         no_grad_vars = [no_grad_vars]
@@ -718,13 +718,13 @@ def to_variable(value, name=None, zero_copy=None, dtype=None):
             y.shape     # [3L, 2L]
 
     """
-    support_type = (list, tuple, np.ndarray, core.VarBase, framework.Variable,
-                    core.Tensor, core.LoDTensor)
+    support_type = (list, tuple, np.ndarray, core.eager.Tensor, core.VarBase,
+                    framework.Variable, core.Tensor, core.LoDTensor)
     if not isinstance(value, support_type):
         raise TypeError(
             "The type of 'value' in fluid.dygraph.to_variable must be %s, but received %s."
             % (support_type, type(value)))
-    if isinstance(value, (core.VarBase, framework.Variable)):
+    if isinstance(value, (core.eager.Tensor, core.VarBase, framework.Variable)):
         return value
     elif isinstance(value, (core.Tensor, core.LoDTensor)):
         return core.VarBase(value)

python/paddle/fluid/dygraph/varbase_patch_methods.py

@@ -28,6 +28,7 @@ from .math_op_patch import monkey_patch_math_varbase
 from .parallel import scale_loss
 from paddle.fluid.data_feeder import convert_dtype, _PADDLE_DTYPE_2_NUMPY_DTYPE
 import paddle.utils.deprecated as deprecated
+from paddle import _C_ops
 
 
 class TensorHookRemoveHelper(object):
@@ -782,7 +783,7 @@ def monkey_patch_varbase():
 
     @framework.dygraph_only
     def clone(self):
-        return _C_ops_.assign(self)
+        return _C_ops.assign(self)
 
     @framework.dygraph_only
     def value(self):

python/paddle/fluid/framework.py

@@ -316,7 +316,8 @@ def _dygraph_not_support_(func):
 
 def _dygraph_only_(func):
     def __impl__(*args, **kwargs):
-        assert in_dygraph_mode(
+        assert (
+            in_dygraph_mode() or _in_eager_mode()
         ), "We only support '%s()' in dynamic graph mode, please call 'paddle.disable_static()' to enter dynamic graph mode." % func.__name__
         return func(*args, **kwargs)
 

python/paddle/fluid/tests/test_detection.py

@@ -886,6 +886,7 @@ class TestDistributeFpnProposals(LayerTest):
                 refer_level=4,
                 refer_scale=224,
                 rois_num=rois_num_dy)
+            print(type(multi_rois_dy))
             output_dy = multi_rois_dy + [restore_ind_dy] + rois_num_per_level_dy
             output_dy_np = []
             for output in output_dy:
@@ -973,4 +974,5 @@ class TestBoxDecoderAndAssign(unittest.TestCase):
 
 
 if __name__ == '__main__':
+    paddle.enable_static()
     unittest.main()

python/paddle/fluid/tests/unittests/distribution/test_distribution_expfamily.py

@@ -50,3 +50,7 @@ class TestExponentialFamilyException(unittest.TestCase):
     def test_entropy_exception(self):
         with self.assertRaises(NotImplementedError):
             paddle.distribution.ExponentialFamily.entropy(self.dist)
+
+
+if __name__ == '__main__':
+    unittest.main()

python/paddle/fluid/tests/unittests/distribution/test_kl.py

@@ -112,3 +112,7 @@ class TestKLExpfamilyExpFamily(unittest.TestCase):
             kl._kl_expfamily_expfamily(self.p, self.q),
             rtol=config.RTOL.get(config.DEFAULT_DTYPE),
             atol=config.ATOL.get(config.DEFAULT_DTYPE))
+
+
+if __name__ == '__main__':
+    unittest.main()

python/paddle/fluid/tests/unittests/sequence/test_sequence_concat.py

@@ -20,6 +20,7 @@ import sys
 sys.path.append("../")
 from op_test import OpTest
 
+import paddle
 from paddle import fluid
 
 
@@ -115,4 +116,5 @@ class TestSequenceConcatOpError(unittest.TestCase):
 
 
 if __name__ == '__main__':
+    paddle.enable_static()
     unittest.main()

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

@@ -39,6 +39,7 @@ class TensorTypeTest(unittest.TestCase):
 
         tensorx = paddle.tensor.logic.Tensor(inx)
         typex_str = str(type(tensorx))
+
         expectx = "<class 'paddle.Tensor'>"
         self.assertEqual((typex_str == expectx), True)
 

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

@@ -1202,4 +1202,5 @@ class TestMultiTensorAdam(unittest.TestCase):
 
 
 if __name__ == "__main__":
+    paddle.enable_static()
     unittest.main()

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

@@ -451,4 +451,5 @@ class TestLayerTo(unittest.TestCase):
 
 
 if __name__ == '__main__':
+    paddle.enable_static()
     unittest.main()

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

@@ -18,6 +18,7 @@ import numpy as np
 import paddle.fluid as fluid
 from paddle.fluid import Program, program_guard
 from paddle.fluid import ParamAttr, initializer
+import paddle
 
 
 class TestCreateParameterError(unittest.TestCase):
@@ -50,4 +51,5 @@ class TestCreateParameterError(unittest.TestCase):
 
 
 if __name__ == '__main__':
+    paddle.enable_static()
     unittest.main()

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

@@ -20,6 +20,7 @@ import numpy as np
 from op_test import OpTest
 from test_softmax_op import stable_softmax
 import paddle.fluid as fluid
+import paddle
 
 
 def CTCAlign(input, lod, blank, merge_repeated, padding=0, input_length=None):
@@ -229,4 +230,5 @@ class BadInputTestCTCAlignr(unittest.TestCase):
 
 
 if __name__ == "__main__":
+    paddle.enable_static()
     unittest.main()

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

@@ -211,4 +211,5 @@ class TestDiffOpPreAppendAxis(TestDiffOp):
 
 
 if __name__ == '__main__':
+    paddle.enable_static()
     unittest.main()

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

@@ -190,4 +190,5 @@ class TestDygraphRemoveWeightNorm(unittest.TestCase):
 
 
 if __name__ == '__main__':
+    paddle.enable_static()
     unittest.main()

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

@@ -209,4 +209,5 @@ class TestExponentialAPI(unittest.TestCase):
 
 
 if __name__ == "__main__":
+    paddle.enable_static()
     unittest.main()

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

@@ -189,3 +189,8 @@ class TestElementwiseFmin2Op(OpTest):
         """test_check_grad_ingore_y"""
         self.check_grad(
             ['X'], 'Out', max_relative_error=0.005, no_grad_set=set('Y'))
+
+
+if __name__ == "__main__":
+    paddle.enable_static()
+    unittest.main()

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

@@ -1025,4 +1025,5 @@ class TestDiracInitializer3(TestDiracInitializer1):
 
 
 if __name__ == '__main__':
+    paddle.enable_static()
     unittest.main()

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

@@ -163,4 +163,5 @@ class TestMultiplyError(unittest.TestCase):
 
 
 if __name__ == '__main__':
+    paddle.enable_static()
     unittest.main()

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

@@ -88,4 +88,5 @@ class TestWhenTrainWithNoGrad(unittest.TestCase):
 
 
 if __name__ == '__main__':
+    paddle.enable_static()
     unittest.main()

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

@@ -210,6 +210,9 @@ class TestIscloseOpFloat64(TestIscloseOp):
         self.atol = np.array([0]).astype("float64")
         self.equal_nan = False
 
+    def test_check_output(self):
+        self.check_output()
+
 
 class TestIscloseOpLargeDimInput(TestIscloseOp):
     def set_args(self):
@@ -222,4 +225,5 @@ class TestIscloseOpLargeDimInput(TestIscloseOp):
 
 
 if __name__ == "__main__":
+    paddle.enable_static()
     unittest.main()

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

@@ -175,4 +175,5 @@ class TestNNFunctionalLogSoftmaxAPI(unittest.TestCase):
 
 
 if __name__ == "__main__":
+    paddle.enable_static()
     unittest.main()

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

@@ -555,4 +555,5 @@ class TestLRScheduler(unittest.TestCase):
 
 
 if __name__ == '__main__':
+    paddle.enable_static()
     unittest.main()

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

@@ -19,6 +19,7 @@ import unittest
 import numpy as np
 from op_test import OpTest
 import paddle.fluid as fluid
+import paddle
 
 
 def compute_mean_iou(predictions, labels, num_classes, in_wrongs, in_corrects,
@@ -129,4 +130,5 @@ class TestMeanIOUOpError(unittest.TestCase):
 
 
 if __name__ == '__main__':
+    paddle.enable_static()
     unittest.main()

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

@@ -17,6 +17,7 @@ from __future__ import print_function
 import unittest
 import numpy as np
 from op_test import OpTest
+import paddle
 
 
 class TestMinusOp(OpTest):
@@ -36,4 +37,5 @@ class TestMinusOp(OpTest):
 
 
 if __name__ == "__main__":
+    paddle.enable_static()
     unittest.main()

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

@@ -588,4 +588,5 @@ class API_NormTest(unittest.TestCase):
 
 
 if __name__ == '__main__':
+    paddle.enable_static()
     unittest.main()

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

@@ -315,7 +315,9 @@ class TestSaveLoadAny(unittest.TestCase):
         paddle.save(tensor, path)
         t_dygraph = paddle.load(path)
         np_dygraph = paddle.load(path, return_numpy=True)
-        self.assertTrue(isinstance(t_dygraph, paddle.fluid.core.VarBase))
+        self.assertTrue(
+            isinstance(t_dygraph, (paddle.fluid.core.VarBase,
+                                   paddle.fluid.core.eager.Tensor)))
         self.assertTrue(np.array_equal(tensor.numpy(), np_dygraph))
         self.assertTrue(np.array_equal(tensor.numpy(), t_dygraph.numpy()))
         paddle.enable_static()
@@ -685,27 +687,34 @@ class TestSaveLoadAny(unittest.TestCase):
                         np.array(v), np.array(load_tensor2['k2'][k])))
             self.assertTrue(load_tensor2['epoch'] == 123)
 
-            self.assertTrue(isinstance(load_tensor3[0], fluid.core.VarBase))
+            self.assertTrue(
+                isinstance(load_tensor3[0], (fluid.core.VarBase,
+                                             fluid.core.eager.Tensor)))
             self.assertTrue(np.array_equal(load_tensor3[0].numpy(), obj3[0]))
-            self.assertTrue(isinstance(load_tensor3[1], fluid.core.VarBase))
+            self.assertTrue(
+                isinstance(load_tensor3[1], (fluid.core.VarBase,
+                                             fluid.core.eager.Tensor)))
             self.assertTrue(np.array_equal(load_tensor3[1].numpy(), obj3[1]))
 
             for k, v in state_dict.items():
                 self.assertTrue(
-                    isinstance(load_tensor3[2]["state_dict"][k],
-                               fluid.core.VarBase))
+                    isinstance(load_tensor3[2]["state_dict"][k], (
+                        fluid.core.VarBase, fluid.core.eager.Tensor)))
                 self.assertTrue(
                     np.array_equal(load_tensor3[2]["state_dict"][k].numpy(),
                                    np.array(v)))
 
             for k, v in state_dict.items():
                 self.assertTrue(
-                    isinstance(load_tensor3[2]["opt"][k], fluid.core.VarBase))
+                    isinstance(load_tensor3[2]["opt"][k], (
+                        fluid.core.VarBase, fluid.core.eager.Tensor)))
                 self.assertTrue(
                     np.array_equal(load_tensor3[2]["opt"][k].numpy(),
                                    np.array(v)))
 
-            self.assertTrue(isinstance(load_tensor4[0], fluid.core.VarBase))
+            self.assertTrue(
+                isinstance(load_tensor4[0], (fluid.core.VarBase,
+                                             fluid.core.eager.Tensor)))
             self.assertTrue(np.array_equal(load_tensor4[0].numpy(), obj4[0]))
 
             load_array1 = paddle.load(path1, return_numpy=True)

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

@@ -54,7 +54,7 @@ class TestRenormAPI(unittest.TestCase):
     def test_dygraph_api(self):
         self.input_data()
         # case axis none
-        with fluid.dygraph.guard():
+        with fluid.dygraph.guard(fluid.CPUPlace()):
             input = [[[2.0, 2, -2], [3, 0.3, 3]], [[2, -8, 2], [3.1, 3.7, 3]]]
             x = paddle.to_tensor(input, stop_gradient=False)
             y = paddle.renorm(x, 1.0, 2, 2.05)
@@ -94,4 +94,5 @@ class TestRenormAPI(unittest.TestCase):
 
 
 if __name__ == '__main__':
+    paddle.enable_static()
     unittest.main()

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

@@ -23,6 +23,7 @@ from test_multiclass_nms_op import iou
 from test_multiclass_nms_op import nms
 import paddle.fluid as fluid
 from paddle.fluid import Program, program_guard
+import paddle
 
 
 def multiclass_nms(prediction, class_num, keep_top_k, nms_threshold):
@@ -518,4 +519,5 @@ class TestRetinanetDetectionOutOpError(unittest.TestCase):
 
 
 if __name__ == '__main__':
+    paddle.enable_static()
     unittest.main()

python/paddle/fluid/tests/unittests/test_smooth_l1_loss.py

@@ -178,4 +178,5 @@ class SmoothL1Loss(unittest.TestCase):
 
 
 if __name__ == "__main__":
+    paddle.enable_static()
     unittest.main()

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

@@ -22,7 +22,7 @@ import paddle.fluid as fluid
 from paddle.fluid import compiler, Program, program_guard
 
 
-# Situation 1: repeat_times is a list (without tensor)
+#Situation 1: repeat_times is a list (without tensor)
 class TestTileOpRank1(OpTest):
     def setUp(self):
         self.op_type = "tile"
@@ -248,4 +248,5 @@ class TestTileAPI(unittest.TestCase):
 
 
 if __name__ == "__main__":
+    paddle.enable_static()
     unittest.main()

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

@@ -1361,4 +1361,5 @@ class TestVarBaseCopyGradientFrom(unittest.TestCase):
 
 
 if __name__ == '__main__':
+    paddle.enable_static()
     unittest.main()

python/paddle/hapi/model.py

@@ -68,8 +68,9 @@ def to_list(value):
 
 
 def to_numpy(var):
-    assert isinstance(var, (Variable, fluid.core.VarBase)), "not a variable"
-    if isinstance(var, fluid.core.VarBase):
+    assert isinstance(var, (Variable, fluid.core.VarBase,
+                            fluid.core.eager.Tensor)), "not a variable"
+    if isinstance(var, (fluid.core.VarBase, fluid.core.eager.Tensor)):
         return var.numpy()
     t = global_scope().find_var(var.name).get_tensor()
     return np.array(t)

python/paddle/metric/metrics.py

@@ -282,7 +282,7 @@ class Accuracy(Metric):
         Return:
             Tensor: the accuracy of current step.
         """
-        if isinstance(correct, paddle.Tensor):
+        if isinstance(correct, (paddle.Tensor, paddle.fluid.core.eager.Tensor)):
             correct = correct.numpy()
         num_samples = np.prod(np.array(correct.shape[:-1]))
         accs = []
@@ -410,12 +410,12 @@ class Precision(Metric):
                 the shape should keep the same as preds.
                 The data type is 'int32' or 'int64'.
         """
-        if isinstance(preds, paddle.Tensor):
+        if isinstance(preds, (paddle.Tensor, paddle.fluid.core.eager.Tensor)):
             preds = preds.numpy()
         elif not _is_numpy_(preds):
             raise ValueError("The 'preds' must be a numpy ndarray or Tensor.")
 
-        if isinstance(labels, paddle.Tensor):
+        if isinstance(labels, (paddle.Tensor, paddle.fluid.core.eager.Tensor)):
             labels = labels.numpy()
         elif not _is_numpy_(labels):
             raise ValueError("The 'labels' must be a numpy ndarray or Tensor.")
@@ -543,12 +543,12 @@ class Recall(Metric):
                 the shape should keep the same as preds.
                 Shape: [batch_size, 1], Dtype: 'int32' or 'int64'.
         """
-        if isinstance(preds, paddle.Tensor):
+        if isinstance(preds, (paddle.Tensor, paddle.fluid.core.eager.Tensor)):
             preds = preds.numpy()
         elif not _is_numpy_(preds):
             raise ValueError("The 'preds' must be a numpy ndarray or Tensor.")
 
-        if isinstance(labels, paddle.Tensor):
+        if isinstance(labels, (paddle.Tensor, paddle.fluid.core.eager.Tensor)):
             labels = labels.numpy()
         elif not _is_numpy_(labels):
             raise ValueError("The 'labels' must be a numpy ndarray or Tensor.")
@@ -698,12 +698,12 @@ class Auc(Metric):
                 (batch_size, 1), labels[i] is either o or 1,
                 representing the label of the instance i.
         """
-        if isinstance(labels, paddle.Tensor):
+        if isinstance(labels, (paddle.Tensor, paddle.fluid.core.eager.Tensor)):
             labels = labels.numpy()
         elif not _is_numpy_(labels):
             raise ValueError("The 'labels' must be a numpy ndarray or Tensor.")
 
-        if isinstance(preds, paddle.Tensor):
+        if isinstance(preds, (paddle.Tensor, paddle.fluid.core.eager.Tensor)):
             preds = preds.numpy()
         elif not _is_numpy_(preds):
             raise ValueError("The 'preds' must be a numpy ndarray or Tensor.")

python/paddle/tensor/logic.py

@@ -462,7 +462,7 @@ def is_tensor(x):
             print(check)  #False
             
     """
-    return isinstance(x, Tensor)
+    return isinstance(x, (Tensor, paddle.fluid.core.eager.Tensor))
 
 
 def _bitwise_op(op_name, x, y, out=None, name=None, binary_op=True):

python/paddle/tensor/manipulation.py

@@ -263,6 +263,9 @@ def fill_diagonal_tensor(x, y, offset=0, dim1=0, dim2=1, name=None):
 
 setattr(core.VarBase, 'fill_diagonal_tensor', fill_diagonal_tensor)
 
+if core._in_eager_mode():
+    setattr(core.eager.Tensor, 'fill_diagonal_tensor', fill_diagonal_tensor)
+
 
 @dygraph_only
 def tolist(x):

python/paddle/tensor/math.py

@@ -1335,7 +1335,7 @@ def renorm(x, p, axis, max_norm):
             raise ValueError("the axis:{} should not be less than -1 * length of input_shape:{}".format(axis,-1 * len(input_shape)))
         axis = axis + len(input_shape)
     if paddle.in_dynamic_mode():
-        out = core.ops.renorm(x, 'p',p, 'axis',axis, 'max_norm', max_norm)
+        out = _C_ops.renorm(x, 'p',p, 'axis',axis, 'max_norm', max_norm)
         return out
 
     inputs = {'X': x}