fix model parallel test, test=allcase

PaddlePaddle · Aug 27, 2021 · babd8a3 · babd8a3 · paddle-bot-old · Aug 27, 2021
1 parent eb9f0dd
commit babd8a3
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Showing 2 changed files with 34 additions and 15 deletions.
diff --git a/python/paddle/fluid/tests/unittests/static_model_parallel_by_col.py b/python/paddle/fluid/tests/unittests/static_model_parallel_by_col.py
@@ -43,29 +43,38 @@
 #fluid.default_main_program().random_seed = 1
 
 
+def get_param_attr(weight, bias):
+    weight_attr = paddle.ParamAttr(
+        initializer=fluid.initializer.NumpyArrayInitializer(weight))
+    bias_attr = paddle.ParamAttr(
+        initializer=fluid.initializer.NumpyArrayInitializer(bias))
+    return weight_attr, bias_attr
+
+
 def create_model(data, rank):
     np.random.seed(2021)
     np_weight = np.random.uniform(-1, 1, size=(IN_SIZE, OUT_SIZE)).astype(DTYPE)
+    np_bias = np.random.uniform(-1, 1, size=(OUT_SIZE, )).astype(DTYPE)
     if rank is not None:
         start_col = 0 if rank == 0 else OUT_SIZE // 2
         np_weight_part = np_weight[:, start_col:start_col + OUT_SIZE // 2]
+        np_bias_part = np_bias[start_col:start_col + OUT_SIZE // 2]
+
+        weight_attr, bias_attr = get_param_attr(np_weight_part, np_bias_part)
         result = paddle.distributed.split(
             data,
             size=(IN_SIZE, OUT_SIZE),
             operation='linear',
             axis=1,
             num_partitions=MODEL_PARALLEL_SIZE,
-            weight_attr=paddle.ParamAttr(
-                initializer=fluid.initializer.NumpyArrayInitializer(
-                    np_weight_part)),
-            bias_attr=False, )
+            weight_attr=weight_attr,
+            bias_attr=bias_attr)
     else:
-        result = fluid.layers.fc(
-            data,
-            size=OUT_SIZE,
-            param_attr=paddle.ParamAttr(
-                initializer=fluid.initializer.NumpyArrayInitializer(np_weight)),
-            bias_attr=False, )
+        weight_attr, bias_attr = get_param_attr(np_weight, np_bias)
+        result = fluid.layers.fc(data,
+                                 size=OUT_SIZE,
+                                 param_attr=weight_attr,
+                                 bias_attr=bias_attr)
 
     predict = paddle.sum(result)
     return predict

diff --git a/python/paddle/fluid/tests/unittests/static_model_parallel_by_row.py b/python/paddle/fluid/tests/unittests/static_model_parallel_by_row.py
@@ -43,29 +43,39 @@
 #fluid.default_main_program().random_seed = 1
 
 
+def get_param_attr(weight, bias):
+    weight_attr = paddle.ParamAttr(
+        initializer=fluid.initializer.NumpyArrayInitializer(weight))
+    bias_attr = paddle.ParamAttr(
+        initializer=fluid.initializer.NumpyArrayInitializer(bias))
+    return weight_attr, bias_attr
+
+
 def create_model(data, rank):
     np.random.seed(2021)
     np_weight = np.random.uniform(-1, 1, size=(IN_SIZE, OUT_SIZE)).astype(DTYPE)
+    np_bias = np.random.uniform(-1, 1, size=(OUT_SIZE, )).astype(DTYPE)
     if rank is not None:
         start_row = 0 if rank == 0 else IN_SIZE // 2
         np_weight_part = np_weight[start_row:start_row + IN_SIZE // 2, :]
+
+        weight_attr, bias_attr = get_param_attr(np_weight_part, np_bias)
         result = paddle.distributed.split(
             data,
             size=(IN_SIZE, OUT_SIZE),
             operation='linear',
             axis=0,
             num_partitions=MODEL_PARALLEL_SIZE,
-            weight_attr=paddle.ParamAttr(
-                initializer=fluid.initializer.NumpyArrayInitializer(
-                    np_weight_part)),
-            bias_attr=False, )
+            weight_attr=weight_attr,
+            bias_attr=bias_attr)
     else:
+        weight_attr, bias_attr = get_param_attr(np_weight, np_bias)
         result = fluid.layers.fc(
             data,
             size=OUT_SIZE,
             param_attr=paddle.ParamAttr(
                 initializer=fluid.initializer.NumpyArrayInitializer(np_weight)),
-            bias_attr=False, )
+            bias_attr=bias_attr)
 
     predict = paddle.sum(result)
     return predict