[Eager] polish several ops (#49612)

* [Eager] polish several ops

* rm useless code

python/paddle/nn/functional/distance.py

@@ -68,9 +68,6 @@ def pairwise_distance(x, y, p=2.0, epsilon=1e-6, keepdim=False, name=None):
     #              [4.99999860, 4.99999860])
 
     """
-    check_type(p, 'porder', (float, int), 'PairwiseDistance')
-    check_type(epsilon, 'epsilon', (float), 'PairwiseDistance')
-    check_type(keepdim, 'keepdim', (bool), 'PairwiseDistance')
     if in_dygraph_mode():
         sub = _C_ops.subtract(x, y)
         # p_norm op has not uesd epsilon, so change it to the following.
@@ -82,6 +79,10 @@ def pairwise_distance(x, y, p=2.0, epsilon=1e-6, keepdim=False, name=None):
         return _C_ops.p_norm(sub, p, -1, 0.0, keepdim, False)
 
     else:
+        check_type(p, 'porder', (float, int), 'PairwiseDistance')
+        check_type(epsilon, 'epsilon', (float), 'PairwiseDistance')
+        check_type(keepdim, 'keepdim', (bool), 'PairwiseDistance')
+
         check_variable_and_dtype(
             x, 'x', ['float32', 'float64'], 'PairwiseDistance'
         )

python/paddle/signal.py

@@ -307,9 +307,6 @@ def stft(
             y1 = stft(x, n_fft=512, center=False, onesided=False)  # [8, 512, 372]
 
     """
-    check_variable_and_dtype(
-        x, 'x', ['float32', 'float64', 'complex64', 'complex128'], 'stft'
-    )
 
     x_rank = len(x.shape)
     assert x_rank in [

python/paddle/tensor/creation.py

@@ -873,7 +873,7 @@ def ones(shape, dtype=None, name=None):
             #  [1. 1.]]
     """
     if dtype is None:
-        dtype = 'float32'
+        dtype = core.VarDesc.VarType.FP32
     return fill_constant(value=1.0, shape=shape, dtype=dtype, name=name)
 
 

python/paddle/tensor/manipulation.py

@@ -1541,14 +1541,6 @@ def flatten(x, start_axis=0, stop_axis=-1, name=None):
     if not (isinstance(x, Variable)):
         raise ValueError("The input x should be a Tensor")
 
-    if not paddle.in_dynamic_mode():
-        check_variable_and_dtype(
-            x,
-            'x',
-            ['float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8'],
-            'flatten',
-        )
-
     x_dim = len(x.shape)
     if x_dim == 0:
         if not (isinstance(start_axis, int)) or start_axis not in [0, -1]:
@@ -1586,6 +1578,12 @@ def flatten(x, start_axis=0, stop_axis=-1, name=None):
     if in_dygraph_mode():
         return _C_ops.flatten(x, start_axis, stop_axis)
     else:
+        check_variable_and_dtype(
+            x,
+            'x',
+            ['float32', 'float64', 'int8', 'int16', 'int32', 'int64', 'uint8'],
+            'flatten',
+        )
         helper = LayerHelper('flatten', **locals())
         out = helper.create_variable_for_type_inference(x.dtype)
         x_shape = helper.create_variable_for_type_inference(x.dtype)

python/paddle/tensor/math.py

@@ -213,6 +213,8 @@ def scale(x, scale=1.0, bias=0.0, bias_after_scale=True, act=None, name=None):
     """
 
     if in_dygraph_mode():
+        if act is None:
+            return _C_ops.scale(x, scale, float(bias), bias_after_scale)
         out = _C_ops.scale(x, scale, float(bias), bias_after_scale)
         return dygraph_utils._append_activation_in_dygraph(out, act)
     else:
@@ -495,6 +497,9 @@ def _elementwise_op_in_dygraph(
                 OP_NAMEMAPPING[op_name] if not is_inplace(op_name) else op_name,
             )
             out = op(x, y)
+    if act is None:
+        return out
+    else:
         return dygraph_utils._append_activation_in_dygraph(
             out, act, use_mkldnn=use_mkldnn
         )
@@ -4209,7 +4214,6 @@ def lerp(x, y, weight, name=None):
 
     """
     if in_dygraph_mode():
-        check_type(weight, 'weight', (float, paddle.Tensor, Variable), 'lerp')
         if isinstance(weight, float):
             weight = paddle.to_tensor(weight, dtype=x.dtype)
 

python/paddle/tensor/random.py

@@ -789,8 +789,8 @@ def randint(low=0, high=None, shape=[1], dtype=None, name=None):
         high = low
         low = 0
     if dtype is None:
-        dtype = 'int64'
-    if not isinstance(dtype, core.VarDesc.VarType):
+        dtype = core.VarDesc.VarType.INT64
+    elif not isinstance(dtype, core.VarDesc.VarType):
         dtype = convert_np_dtype_to_dtype_(dtype)
 
     if in_dygraph_mode():