fix XPU unittest problem for shape check (#54365)

python/paddle/tensor/__init__.py

@@ -348,6 +348,7 @@ tensor_method_func = [  # noqa
     'logit',
     'exp',
     'exp_',
+    'expm1',
     'floor',
     'floor_',
     'increment',

test/xpu/test_accuracy_op_xpu.py

@@ -48,11 +48,9 @@ class XPUTestAccuracyOp(XPUOpTestWrapper):
                         num_correct += 1
                         break
             self.outputs = {
-                'Accuracy': np.array([num_correct / float(n)]).astype(
-                    self.dtype
-                ),
-                'Correct': np.array([num_correct]).astype("int32"),
-                'Total': np.array([n]).astype("int32"),
+                'Accuracy': np.array(num_correct / float(n)).astype(self.dtype),
+                'Correct': np.array(num_correct).astype("int32"),
+                'Total': np.array(n).astype("int32"),
             }
             self.attrs = {'use_xpu': True}
 

test/xpu/test_expand_as_v2_op_xpu.py

@@ -93,7 +93,7 @@ class XPUTestExpandAsV2Op(XPUOpTestWrapper):
         def set_inputs(self):
             x = np.random.rand(1, 1, 7, 16).astype(self.dtype)
             self.inputs = {'X': x}
-            target_tensor = np.random.rand(1, 1, 7, 16).astype(self.dtype)
+            target_tensor = np.random.rand(4, 6, 7, 16).astype(self.dtype)
             self.attrs = {'target_shape': target_tensor.shape}
 
         def set_output(self):
@@ -105,7 +105,7 @@ class XPUTestExpandAsV2Op(XPUOpTestWrapper):
         def set_inputs(self):
             x = np.random.rand(1, 1, 7, 16, 1).astype(self.dtype)
             self.inputs = {'X': x}
-            target_tensor = np.random.rand(1, 1, 7, 16, 1).astype(self.dtype)
+            target_tensor = np.random.rand(4, 6, 7, 16, 1).astype(self.dtype)
             self.attrs = {'target_shape': target_tensor.shape}
 
         def set_output(self):
@@ -117,7 +117,7 @@ class XPUTestExpandAsV2Op(XPUOpTestWrapper):
         def set_inputs(self):
             x = np.random.rand(1, 1, 7, 16, 1, 1).astype(self.dtype)
             self.inputs = {'X': x}
-            target_tensor = np.random.rand(1, 1, 7, 16, 1, 1).astype(self.dtype)
+            target_tensor = np.random.rand(4, 6, 7, 16, 1, 1).astype(self.dtype)
             self.attrs = {'target_shape': target_tensor.shape}
 
         def set_output(self):
@@ -129,8 +129,8 @@ class XPUTestExpandAsV2Op(XPUOpTestWrapper):
 # Test python API
 class TestExpandAsV2API(unittest.TestCase):
     def test_api(self):
-        input1 = np.random.random([12, 14]).astype("float32")
-        input2 = np.random.random([2, 12, 14]).astype("float32")
+        x_np = np.random.random([12, 14]).astype("float32")
+        y_np = np.random.random([2, 12, 14]).astype("float32")
         x = paddle.static.data(name='x', shape=[12, 14], dtype="float32")
 
         y = paddle.static.data(
@@ -144,10 +144,10 @@ class TestExpandAsV2API(unittest.TestCase):
         exe = fluid.Executor(place=fluid.XPUPlace(0))
         res_1 = exe.run(
             fluid.default_main_program(),
-            feed={"x": input1, "target_tensor": input2},
+            feed={"x": x_np, "target_tensor": y_np},
             fetch_list=[out_1],
         )
-        assert np.array_equal(res_1[0], np.tile(input1, (2, 1, 1)))
+        assert np.array_equal(res_1[0], np.tile(x_np, (2, 1, 1)))
 
 
 support_types = get_xpu_op_support_types('expand_as_v2')

test/xpu/test_gather_nd_op_xpu.py

@@ -81,13 +81,13 @@ class XPUTestGatherNd(XPUOpTestWrapper):
         def init_data(self):
             self.xnp = np.random.random((5, 20)).astype(self.in_type)
             self.inp = np.array([1]).astype("int32")
-            self.output = self.xnp[self.inp]
+            self.output = self.xnp[tuple(self.inp)]
 
     class XPUTestGatherNdOpWithIndex2(XPUTestGatherNdBase):
         def init_data(self):
             self.xnp = np.random.random((5, 20)).astype(self.in_type)
             self.inp = np.array([1]).astype("int64")
-            self.output = self.xnp[self.inp]
+            self.output = self.xnp[tuple(self.inp)]
 
     class XPUTestGatherNdOpWithLowIndex1(XPUTestGatherNdBase):
         def init_data(self):

test/xpu/test_nll_loss_op_xpu.py

@@ -45,16 +45,16 @@ def nll_loss_1d(
         out[i] = -logs[i][cur_target] * cur_weight
     if reduction == 'sum':
         out = np.sum(out)
-        total_weight = np.array([total_weight]).astype(dtype)
+        total_weight = np.array(total_weight).astype(dtype)
         return {'Out': out, 'Total_weight': total_weight}
     elif reduction == 'mean':
         out = np.sum(out)
         if total_weight != 0:
             out /= total_weight
-        total_weight = np.array([total_weight]).astype(dtype)
+        total_weight = np.array(total_weight).astype(dtype)
         return {'Out': out, 'Total_weight': total_weight}
     elif reduction == 'none':
-        total_weight = np.array([0]).astype(dtype)
+        total_weight = np.array(0).astype(dtype)
         return {'Out': out, 'Total_weight': total_weight}
 
 
@@ -79,16 +79,16 @@ def nll_loss_2d(
                 out[i][h][w] = -logs[i][cur_target][h][w] * cur_weight
     if reduction == 'sum':
         out = np.sum(out)
-        total_weight = np.array([total_weight]).astype(dtype)
+        total_weight = np.array(total_weight).astype(dtype)
         return {'Out': out, 'Total_weight': total_weight}
     elif reduction == 'mean':
         out = np.sum(out)
         if total_weight != 0:
             out /= total_weight
-        total_weight = np.array([total_weight]).astype(dtype)
+        total_weight = np.array(total_weight).astype(dtype)
         return {'Out': out, 'Total_weight': total_weight}
     elif reduction == 'none':
-        total_weight = np.array([0]).astype(dtype)
+        total_weight = np.array(0).astype(dtype)
         return {'Out': out, 'Total_weight': total_weight}
 
 

test/xpu/test_reduce_any_op_xpu.py

@@ -40,8 +40,8 @@ class XPUTestReduceAnyOp(XPUOpTestWrapper):
             self.op_type = 'reduce_any'
             self.attrs = {
                 'use_xpu': True,
-                'reduce_all': True,
-                'keep_dim': True,
+                'reduce_all': False,
+                'keep_dim': False,
                 'dim': (3, 5, 4),
             }
             self.inputs = {
@@ -76,7 +76,7 @@ class XPUTestReduceAnyOp(XPUOpTestWrapper):
             self.op_type = 'reduce_any'
             self.attrs = {
                 'use_xpu': True,
-                'reduce_all': True,
+                'reduce_all': False,
                 'keep_dim': False,
                 'dim': (3, 6),
             }

test/xpu/test_size_op_xpu.py

@@ -43,7 +43,7 @@ class XPUTestSizeOP(XPUOpTestWrapper):
             self.inputs = {
                 'Input': x,
             }
-            self.outputs = {'Out': np.array([np.size(x)])}
+            self.outputs = {'Out': np.array(np.size(x))}
 
         def initTestCase(self):
             self.shape = (6, 56, 8, 55)

test/xpu/test_unbind_op_xpu.py

@@ -97,7 +97,9 @@ class XPUTestUnbindOP(XPUOpTestWrapper):
             pass
 
         def outReshape(self):
-            pass
+            self.out[0] = self.out[0].reshape((2, 2))
+            self.out[1] = self.out[1].reshape((2, 2))
+            self.out[2] = self.out[2].reshape((2, 2))
 
         def setAxis(self):
             pass

test/xpu/test_where_index_xpu.py

@@ -58,7 +58,7 @@ class XPUTestWhereIndexOp(XPUOpTestWrapper):
             self.inputs = {
                 'Condition': np.array([False, False, False]).astype(self.dtype),
             }
-            self.outputs = {'Out': np.array([], dtype='int64')}
+            self.outputs = {'Out': np.array([], dtype='int64').reshape(0, 1)}
 
     class TestRank2(TestWhereIndexOp):
         def init_data(self):