[tests] clean paddle.paddle (PaddlePaddle#60380)

Wanglongzhi2001 · Jan 7, 2024 · 6783f63 · 6783f63
1 parent bdbbfe7
commit 6783f63
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Showing 9 changed files with 15 additions and 15 deletions.
diff --git a/python/paddle/incubate/optimizer/functional/utils.py b/python/paddle/incubate/optimizer/functional/utils.py
@@ -72,7 +72,7 @@ def false_fn():
         paddle.static.nn.cond(is_symmetric, None, false_fn)
         # eigvals only support cpu
         paddle.set_device("cpu")
-        eigvals = paddle.paddle.linalg.eigvals(H0)
+        eigvals = paddle.linalg.eigvals(H0)
         is_positive = paddle.all(eigvals.real() > 0.0) and paddle.all(
             eigvals.imag() == 0.0
         )

diff --git a/test/auto_parallel/test_auto_conditional_block.py b/test/auto_parallel/test_auto_conditional_block.py
@@ -80,7 +80,7 @@ def forward(self, input):
 
 
 def loss_func(pred, label):
-    error_cost = paddle.paddle.nn.functional.square_error_cost(pred, label)
+    error_cost = paddle.nn.functional.square_error_cost(pred, label)
     error_cost = error_cost[error_cost > 0].astype("float32")
     loss = paddle.mean(error_cost)
     return loss

diff --git a/test/ipu/test_dy2static_fp16_ipu.py b/test/ipu/test_dy2static_fp16_ipu.py
@@ -34,7 +34,7 @@ def forward(self, x, target=None):
         x = paddle.flatten(x, 1, -1)
         if target is not None:
             x = paddle.nn.functional.softmax(x)
-            loss = paddle.paddle.nn.functional.cross_entropy(
+            loss = paddle.nn.functional.cross_entropy(
                 x, target, reduction='none', use_softmax=False
             )
             if self.use_ipu:

diff --git a/test/ipu/test_dy2static_ipu.py b/test/ipu/test_dy2static_ipu.py
@@ -49,7 +49,7 @@ def forward(self, x, target=None):
         if target is not None:
             if self.use_softmax:
                 x = paddle.nn.functional.softmax(x)
-            loss = paddle.paddle.nn.functional.cross_entropy(
+            loss = paddle.nn.functional.cross_entropy(
                 x, target, reduction='none', use_softmax=False
             )
             if self.use_reduction:
@@ -219,7 +219,7 @@ def create_model(self, use_ipu=False):
 
 class TestWithoutIdentityLoss2(TestBase):
     def set_op_attrs(self):
-        self.loss_op = paddle.paddle.nn.functional.softmax_with_cross_entropy
+        self.loss_op = paddle.nn.functional.softmax_with_cross_entropy
 
     def set_data_feed(self):
         self.data = paddle.uniform((8, 3, 10, 10), dtype='float32')

diff --git a/test/ipu/test_modelruntime_ipu.py b/test/ipu/test_modelruntime_ipu.py
@@ -33,7 +33,7 @@ def forward(self, x, target=None):
         x = paddle.flatten(x, 1, -1)
         if target is not None:
             x = paddle.nn.functional.softmax(x)
-            loss = paddle.paddle.nn.functional.cross_entropy(
+            loss = paddle.nn.functional.cross_entropy(
                 x, target, reduction='none', use_softmax=False
             )
             return x, loss

diff --git a/test/ipu/test_print_op_ipu.py b/test/ipu/test_print_op_ipu.py
@@ -120,7 +120,7 @@ def forward(self, x, target=None):
         x = paddle.flatten(x, 1, -1)
         if target is not None:
             x = paddle.nn.functional.softmax(x)
-            loss = paddle.paddle.nn.functional.cross_entropy(
+            loss = paddle.nn.functional.cross_entropy(
                 x, target, reduction='none', use_softmax=False
             )
             loss = paddle.incubate.identity_loss(loss, 1)

diff --git a/test/legacy_test/test_conv2d_transpose_op.py b/test/legacy_test/test_conv2d_transpose_op.py
@@ -1349,7 +1349,7 @@ def var_prefix(self):
     def call_func(self, x):
         w_var = paddle.randn((3, 6, 3, 3), dtype='float32')
         output_size = paddle.assign([17])
-        out = paddle.paddle.nn.functional.conv2d_transpose(
+        out = paddle.nn.functional.conv2d_transpose(
             x, w_var, stride=2, output_size=output_size
         )
         return out
@@ -1388,7 +1388,7 @@ def path_prefix(self):
     def call_func(self, x):
         w_var = paddle.randn((3, 6, 3, 3), dtype='float32')
         output_size = [17, paddle.assign([17])]
-        out = paddle.paddle.nn.functional.conv2d_transpose(
+        out = paddle.nn.functional.conv2d_transpose(
             x, w_var, stride=2, output_size=output_size
         )
         return out

diff --git a/test/legacy_test/test_dist_fleet_a_sync_optimizer_auto_async.py b/test/legacy_test/test_dist_fleet_a_sync_optimizer_auto_async.py
@@ -58,7 +58,7 @@ def test_a_sync_optimizer3(self):
             size=[1000000000, 100000],
             param_attr=paddle.base.ParamAttr(
                 name="embedding",
-                initializer=paddle.paddle.nn.initializer.Constant(value=0.01),
+                initializer=paddle.nn.initializer.Constant(value=0.01),
             ),
             is_sparse=True,
         )

diff --git a/test/legacy_test/test_fused_multi_transformer_op.py b/test/legacy_test/test_fused_multi_transformer_op.py
@@ -60,7 +60,7 @@ def setUp(self):
         self.__class__.no_need_check_grad = False
 
         bias_attr = paddle.base.ParamAttr(
-            initializer=paddle.paddle.nn.initializer.Constant(value=0.0005)
+            initializer=paddle.nn.initializer.Constant(value=0.0005)
         )
         self.q_proj = Linear(
             self.embed_dim,
@@ -1383,16 +1383,16 @@ def config(self):
         self.has_attn_mask = False
         self.x_type = np.float32
         self.weight_attr = paddle.ParamAttr(
-            initializer=paddle.paddle.nn.initializer.Constant(0.0)
+            initializer=paddle.nn.initializer.Constant(0.0)
         )
         self.bias_attr = paddle.ParamAttr(
-            initializer=paddle.paddle.nn.initializer.Constant(0.0005)
+            initializer=paddle.nn.initializer.Constant(0.0005)
         )
         self.ln_w_attr = paddle.ParamAttr(
-            initializer=paddle.paddle.nn.initializer.Constant(1.0)
+            initializer=paddle.nn.initializer.Constant(1.0)
         )
         self.ln_b_attr = paddle.ParamAttr(
-            initializer=paddle.paddle.nn.initializer.Constant(0.0)
+            initializer=paddle.nn.initializer.Constant(0.0)
         )
 
     def test_fused_multi_transformer_op(self):