diff --git a/python/paddle/fluid/tests/unittests/parallel_executor_test_base.py b/python/paddle/fluid/tests/unittests/parallel_executor_test_base.py index 0d0e118e6e42b00067c5b08c5fe9a16e6c7a3538..47f5c5085a027a6f0831cc1de51223e821059257 100644 --- a/python/paddle/fluid/tests/unittests/parallel_executor_test_base.py +++ b/python/paddle/fluid/tests/unittests/parallel_executor_test_base.py @@ -28,19 +28,14 @@ import sys from feed_data_reader import FeedDataReader __all__ = ['TestParallelExecutorBase'] - - -class DeviceType: - CPU = 1 - GPU = 2 - XPU = 3 +DeviceType = core.DeviceType class TestParallelExecutorBase(unittest.TestCase): @classmethod def check_network_convergence(cls, method, - use_device=DeviceType.GPU, + use_device=DeviceType.CUDA, iter=5, batch_size=None, feed_dict=None, @@ -81,7 +76,7 @@ class TestParallelExecutorBase(unittest.TestCase): main, method, optimizer) place = fluid.CUDAPlace( - 0) if use_device == DeviceType.GPU else fluid.XPUPlace( + 0) if use_device == DeviceType.CUDA else fluid.XPUPlace( 0) if use_device == DeviceType.XPU else fluid.CPUPlace() exe = fluid.Executor(place) exe.run(startup) @@ -102,7 +97,7 @@ class TestParallelExecutorBase(unittest.TestCase): if batch_size is not None: batch_size *= fluid.core.get_cuda_device_count( - ) if use_device == DeviceType.GPU else fluid.core.get_xpu_device_count( + ) if use_device == DeviceType.CUDA else fluid.core.get_xpu_device_count( ) if use_device == DeviceType.XPU else int( os.environ.get('CPU_NUM', multiprocessing.cpu_count())) @@ -132,7 +127,7 @@ class TestParallelExecutorBase(unittest.TestCase): @classmethod def check_pass_conflict(cls, method, - use_device=DeviceType.GPU, + use_device=DeviceType.CUDA, feed_dict=None, get_data_from_feeder=None, use_reduce=False, @@ -153,7 +148,7 @@ class TestParallelExecutorBase(unittest.TestCase): main, method, optimizer) place = fluid.CUDAPlace( - 0) if use_device == DeviceType.GPU else fluid.XPUPlace( + 0) if use_device == DeviceType.CUDA else fluid.XPUPlace( 0) if use_device == DeviceType.XPU else fluid.CPUPlace() exe = fluid.Executor(place) exe.run(startup) @@ -191,7 +186,7 @@ class TestParallelExecutorBase(unittest.TestCase): build_strategy.enable_inplace = enable_inplace build_strategy.enable_sequential_execution = enable_sequential_execution - if use_device == DeviceType.GPU and core.is_compiled_with_cuda(): + if use_device == DeviceType.CUDA and core.is_compiled_with_cuda(): build_strategy.remove_unnecessary_lock = True if use_device == DeviceType.XPU and core.is_compiled_with_xpu(): build_strategy.fuse_elewise_add_act_ops = False diff --git a/python/paddle/fluid/tests/unittests/seresnext_net.py b/python/paddle/fluid/tests/unittests/seresnext_net.py index d20cf70b14a6c85bc2473fe35fcb8184102ef8cc..2e4b1828c5bbe67f2fb5ba76183138bb152f4963 100644 --- a/python/paddle/fluid/tests/unittests/seresnext_net.py +++ b/python/paddle/fluid/tests/unittests/seresnext_net.py @@ -171,20 +171,20 @@ model = SE_ResNeXt50Small def batch_size(use_device): - if use_device == DeviceType.GPU: + if use_device == DeviceType.CUDA: # Paddle uses 8GB P4 GPU for unittest so we decreased the batch size. return 8 return 12 def iter(use_device): - if use_device == DeviceType.GPU: + if use_device == DeviceType.CUDA: return 10 return 1 gpu_img, gpu_label = init_data( - batch_size=batch_size(use_device=DeviceType.GPU), + batch_size=batch_size(use_device=DeviceType.CUDA), img_shape=img_shape, label_range=999) cpu_img, cpu_label = init_data( @@ -196,6 +196,6 @@ feed_dict_cpu = {"image": cpu_img, "label": cpu_label} def feed_dict(use_device): - if use_device == DeviceType.GPU: + if use_device == DeviceType.CUDA: return feed_dict_gpu return feed_dict_cpu diff --git a/python/paddle/fluid/tests/unittests/seresnext_test_base.py b/python/paddle/fluid/tests/unittests/seresnext_test_base.py index a39ca59b656f68191ec7798daac3ee5ad1269532..cc40b89b585cbf8795a06ee4c5c557b162b0651f 100644 --- a/python/paddle/fluid/tests/unittests/seresnext_test_base.py +++ b/python/paddle/fluid/tests/unittests/seresnext_test_base.py @@ -26,7 +26,7 @@ class TestResnetBase(TestParallelExecutorBase): use_device, delta2=1e-5, compare_seperately=True): - if use_device == DeviceType.GPU and not core.is_compiled_with_cuda(): + if use_device == DeviceType.CUDA and not core.is_compiled_with_cuda(): return func_1_first_loss, func_1_last_loss = self.check_network_convergence( diff --git a/python/paddle/fluid/tests/unittests/test_fuse_all_reduce_pass.py b/python/paddle/fluid/tests/unittests/test_fuse_all_reduce_pass.py index aa520beb2014f8a763a47d65fba7b0eae465f6b2..881b9d905799f241931a20227b998ca10b8b35c0 100644 --- a/python/paddle/fluid/tests/unittests/test_fuse_all_reduce_pass.py +++ b/python/paddle/fluid/tests/unittests/test_fuse_all_reduce_pass.py @@ -35,7 +35,7 @@ class TestFuseAllReduceOpsBase(TestParallelExecutorBase): get_data_from_feeder=None, optimizer=None, fuse_all_optimizer_ops=False): - if use_device == DeviceType.GPU and not core.is_compiled_with_cuda(): + if use_device == DeviceType.CUDA and not core.is_compiled_with_cuda(): return feed_dict_data = None @@ -82,12 +82,12 @@ class TestFuseAllReduceOps(TestFuseAllReduceOpsBase): fuse_all_optimizer_ops=True) def test_simple_fc_with_fuse_all_reduce(self): - self._decorate_compare_fused_all_reduce(simple_fc_net, DeviceType.GPU) + self._decorate_compare_fused_all_reduce(simple_fc_net, DeviceType.CUDA) self._decorate_compare_fused_all_reduce(simple_fc_net, DeviceType.CPU) def test_batchnorm_fc_with_fuse_all_reduce(self): self._decorate_compare_fused_all_reduce(fc_with_batchnorm, - DeviceType.GPU) + DeviceType.CUDA) self._decorate_compare_fused_all_reduce(fc_with_batchnorm, DeviceType.CPU) @@ -126,7 +126,7 @@ class TestFuseAllReduceOpsWithSparseGrad(TestFuseAllReduceOpsBase): def test_simple_bow_net_with_fuse_all_reduce(self): model = partial(bow_net, dict_dim=self.word_dict_len, is_sparse=True) - self._decorate_compare_fused_all_reduce(model, DeviceType.GPU) + self._decorate_compare_fused_all_reduce(model, DeviceType.CUDA) self._decorate_compare_fused_all_reduce(model, DeviceType.CPU) diff --git a/python/paddle/fluid/tests/unittests/test_fuse_elewise_add_act_pass.py b/python/paddle/fluid/tests/unittests/test_fuse_elewise_add_act_pass.py index e5e8eee6f848a1c37414e0bee870559da5e9c65c..a1c20be9a92f83d67e934eeaf84b95c2fac0b579 100644 --- a/python/paddle/fluid/tests/unittests/test_fuse_elewise_add_act_pass.py +++ b/python/paddle/fluid/tests/unittests/test_fuse_elewise_add_act_pass.py @@ -26,7 +26,7 @@ class TestMNIST(TestParallelExecutorBase): os.environ['CPU_NUM'] = str(4) def _compare_fuse_elewise_add_act_ops(self, model, use_device): - if use_device == DeviceType.GPU and not core.is_compiled_with_cuda(): + if use_device == DeviceType.CUDA and not core.is_compiled_with_cuda(): return img, label = init_data() @@ -66,12 +66,12 @@ class TestMNIST(TestParallelExecutorBase): self.assertAlmostEquals(loss[0], loss[1], delta=1e-6) def test_simple_fc_with_fuse_op(self): - self._compare_fuse_elewise_add_act_ops(simple_fc_net, DeviceType.GPU) + self._compare_fuse_elewise_add_act_ops(simple_fc_net, DeviceType.CUDA) self._compare_fuse_elewise_add_act_ops(simple_fc_net, DeviceType.CPU) def test_batchnorm_fc_with_fuse_op(self): self._compare_fuse_elewise_add_act_ops(fc_with_batchnorm, - DeviceType.GPU) + DeviceType.CUDA) self._compare_fuse_elewise_add_act_ops(fc_with_batchnorm, DeviceType.CPU) diff --git a/python/paddle/fluid/tests/unittests/test_fuse_optimizer_pass.py b/python/paddle/fluid/tests/unittests/test_fuse_optimizer_pass.py index 75aa07c4b9b7e0d26f9372d32f133ebda5c16357..51c06bb79d72872aabe7561b504a2ce50eb3433e 100644 --- a/python/paddle/fluid/tests/unittests/test_fuse_optimizer_pass.py +++ b/python/paddle/fluid/tests/unittests/test_fuse_optimizer_pass.py @@ -38,7 +38,7 @@ class TestFuseOptimizationOps(TestParallelExecutorBase): feed_dict=None, get_data_from_feeder=None, optimizer=fluid.optimizer.Adam): - if use_device == DeviceType.GPU and not core.is_compiled_with_cuda(): + if use_device == DeviceType.CUDA and not core.is_compiled_with_cuda(): return not_fuse_op_first_loss, not_fuse_op_last_loss = self.check_network_convergence( @@ -76,7 +76,7 @@ class TestFuseAdamOps(TestFuseOptimizationOps): def test_batchnorm_fc_with_fuse_op(self): self._decorate_compare_fused_optimizer_ops( - fc_with_batchnorm, DeviceType.GPU, optimizer=self.optimizer) + fc_with_batchnorm, DeviceType.CUDA, optimizer=self.optimizer) self._decorate_compare_fused_optimizer_ops( fc_with_batchnorm, DeviceType.CPU, optimizer=self.optimizer) @@ -121,7 +121,7 @@ class TestSpareFuseAdamOps(TestFuseOptimizationOps): def test_simple_bow_net_with_fuse_op(self): model = partial(bow_net, dict_dim=self.word_dict_len, is_sparse=True) self._decorate_compare_fused_optimizer_ops( - model, DeviceType.GPU, optimizer=self.optimizer) + model, DeviceType.CUDA, optimizer=self.optimizer) self._decorate_compare_fused_optimizer_ops( model, DeviceType.CPU, optimizer=self.optimizer) @@ -144,7 +144,7 @@ class TestPassConflictBase(TestFuseAdamOps): feed_dict=None, get_data_from_feeder=None, optimizer=fluid.optimizer.Adam): - if use_device == DeviceType.GPU and not core.is_compiled_with_cuda(): + if use_device == DeviceType.CUDA and not core.is_compiled_with_cuda(): return self.check_pass_conflict( @@ -165,7 +165,7 @@ class TestFuseAdamOpsPassConflict(TestPassConflictBase): self._decorate_compare_fused_optimizer_ops( fc_with_batchnorm, DeviceType.CPU, optimizer=self.optimizer) self._decorate_compare_fused_optimizer_ops( - fc_with_batchnorm, DeviceType.GPU, optimizer=self.optimizer) + fc_with_batchnorm, DeviceType.CUDA, optimizer=self.optimizer) class TestFuseSGDOpsPassConflict(TestFuseAdamOpsPassConflict): diff --git a/python/paddle/fluid/tests/unittests/test_fuse_relu_depthwise_conv_pass.py b/python/paddle/fluid/tests/unittests/test_fuse_relu_depthwise_conv_pass.py index 0e54ebc7f4567afcafe306fcc082b56b4b3abadb..9b739ebdfb23c680a86a54a3fa00398805ee8968 100644 --- a/python/paddle/fluid/tests/unittests/test_fuse_relu_depthwise_conv_pass.py +++ b/python/paddle/fluid/tests/unittests/test_fuse_relu_depthwise_conv_pass.py @@ -73,7 +73,7 @@ class TestMNIST(TestParallelExecutorBase): return img, label def _compare(self, model, use_device, random_data=True, only_forward=False): - if use_device == DeviceType.GPU and not core.is_compiled_with_cuda(): + if use_device == DeviceType.CUDA and not core.is_compiled_with_cuda(): return img, label = self._init_data(random_data) @@ -108,11 +108,11 @@ class TestMNIST(TestParallelExecutorBase): self.assertAlmostEquals(loss[0], loss[1], delta=1e-6) def test_simple_depthwise_with_fuse_op(self): - self._compare(simple_depthwise_net, DeviceType.GPU) + self._compare(simple_depthwise_net, DeviceType.CUDA) self._compare(simple_depthwise_net, DeviceType.CPU) def test_simple_depthwise_with_fuse_op_only_forward(self): - self._compare(simple_depthwise_net, DeviceType.GPU, only_forward=True) + self._compare(simple_depthwise_net, DeviceType.CUDA, only_forward=True) self._compare(simple_depthwise_net, DeviceType.CPU, only_forward=True) diff --git a/python/paddle/fluid/tests/unittests/test_ir_inplace_pass.py b/python/paddle/fluid/tests/unittests/test_ir_inplace_pass.py index f8b2ec21bc5fa78df32804bd7968b68c33fac063..e2094c76b7d1b24ba03362305a7a0fea337f9efd 100644 --- a/python/paddle/fluid/tests/unittests/test_ir_inplace_pass.py +++ b/python/paddle/fluid/tests/unittests/test_ir_inplace_pass.py @@ -58,7 +58,7 @@ class TestIrInplace(TestParallelExecutorBase): fc_with_batchnorm, feed_dict={"image": img, "label": label}, - use_device=DeviceType.GPU, + use_device=DeviceType.CUDA, use_ir_memory_optimize=ir_memory_optimize, enable_inplace=enable_inplace) diff --git a/python/paddle/fluid/tests/unittests/test_ir_memory_optimize_pass.py b/python/paddle/fluid/tests/unittests/test_ir_memory_optimize_pass.py index 61ceefdad11a9a9c8c8983532e73272a0a9b53fd..f4ec63a8b916e55675f8d5c716a95b57013d994f 100644 --- a/python/paddle/fluid/tests/unittests/test_ir_memory_optimize_pass.py +++ b/python/paddle/fluid/tests/unittests/test_ir_memory_optimize_pass.py @@ -61,7 +61,7 @@ class TestMNIST(TestParallelExecutorBase): return img, label def _compare_ir_memory_optimize(self, model, use_device): - if use_device == DeviceType.GPU and not core.is_compiled_with_cuda(): + if use_device == DeviceType.CUDA and not core.is_compiled_with_cuda(): return img, label = self._dummy_data() @@ -84,11 +84,11 @@ class TestMNIST(TestParallelExecutorBase): def test_simple_fc_net(self): self._compare_ir_memory_optimize(simple_fc_net, DeviceType.CPU) - self._compare_ir_memory_optimize(simple_fc_net, DeviceType.GPU) + self._compare_ir_memory_optimize(simple_fc_net, DeviceType.CUDA) def test_fc_with_reshape_net(self): self._compare_ir_memory_optimize(fc_with_inplace_net, DeviceType.CPU) - self._compare_ir_memory_optimize(fc_with_inplace_net, DeviceType.GPU) + self._compare_ir_memory_optimize(fc_with_inplace_net, DeviceType.CUDA) if __name__ == '__main__': diff --git a/python/paddle/fluid/tests/unittests/test_ir_memory_optimize_transformer.py b/python/paddle/fluid/tests/unittests/test_ir_memory_optimize_transformer.py index 40c4fa749536e74f5cdcc2aadb59479ef55d9a16..aa495c7533ce017debdc2fa4cc899b016e7e418d 100644 --- a/python/paddle/fluid/tests/unittests/test_ir_memory_optimize_transformer.py +++ b/python/paddle/fluid/tests/unittests/test_ir_memory_optimize_transformer.py @@ -35,14 +35,14 @@ class TestTransformerWithIR(TestParallelExecutorBase): # check python transpiler self.check_network_convergence( transformer, - use_device=DeviceType.GPU, + use_device=DeviceType.CUDA, feed_data_reader=get_feed_data_reader(), use_ir_memory_optimize=False, iter=2) # check IR memory optimize self.check_network_convergence( transformer, - use_device=DeviceType.GPU, + use_device=DeviceType.CUDA, feed_data_reader=get_feed_data_reader(), use_ir_memory_optimize=True, iter=2) diff --git a/python/paddle/fluid/tests/unittests/test_mix_precision_all_reduce_fuse.py b/python/paddle/fluid/tests/unittests/test_mix_precision_all_reduce_fuse.py index 7df3583f0d29a14c481df9e44c2f09204f71b2af..33393bc2fcd20fb26abed506564392650e3b6496 100644 --- a/python/paddle/fluid/tests/unittests/test_mix_precision_all_reduce_fuse.py +++ b/python/paddle/fluid/tests/unittests/test_mix_precision_all_reduce_fuse.py @@ -84,7 +84,7 @@ class TestResnet(TestParallelExecutorBase): def test_model(self): if core.is_compiled_with_cuda(): - self.check_model(DeviceType.GPU) + self.check_model(DeviceType.CUDA) if __name__ == '__main__': diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor_mnist.py b/python/paddle/fluid/tests/unittests/test_parallel_executor_mnist.py index 305c7703be8c7e6b817e0fad783e5f6ed1e44a2f..2c79670f1a27cda72475e474fa992a1a5da987e3 100644 --- a/python/paddle/fluid/tests/unittests/test_parallel_executor_mnist.py +++ b/python/paddle/fluid/tests/unittests/test_parallel_executor_mnist.py @@ -81,7 +81,7 @@ class TestMNIST(TestParallelExecutorBase): use_device, delta1=1e-6, delta2=1e-4): - if use_device == DeviceType.GPU and not core.is_compiled_with_cuda(): + if use_device == DeviceType.CUDA and not core.is_compiled_with_cuda(): return if use_device == DeviceType.XPU and not core.is_compiled_with_xpu(): @@ -110,7 +110,7 @@ class TestMNIST(TestParallelExecutorBase): # simple_fc def check_simple_fc_convergence(self, use_device, use_reduce=False): - if use_device == DeviceType.GPU and not core.is_compiled_with_cuda(): + if use_device == DeviceType.CUDA and not core.is_compiled_with_cuda(): return if use_device == DeviceType.XPU and not core.is_compiled_with_xpu(): @@ -127,7 +127,7 @@ class TestMNIST(TestParallelExecutorBase): def test_simple_fc(self): # use_device - self.check_simple_fc_convergence(DeviceType.GPU) + self.check_simple_fc_convergence(DeviceType.CUDA) self.check_simple_fc_convergence(DeviceType.CPU) self.check_simple_fc_convergence(DeviceType.XPU) @@ -135,13 +135,13 @@ class TestMNIST(TestParallelExecutorBase): # use_device, use_reduce # NOTE: the computation result of nccl_reduce is non-deterministic, # related issue: https://github.com/NVIDIA/nccl/issues/157 - self._compare_reduce_and_allreduce(simple_fc_net, DeviceType.GPU, 1e-5, + self._compare_reduce_and_allreduce(simple_fc_net, DeviceType.CUDA, 1e-5, 1e-2) self._compare_reduce_and_allreduce(simple_fc_net, DeviceType.CPU, 1e-5, 1e-2) def check_simple_fc_parallel_accuracy(self, use_device): - if use_device == DeviceType.GPU and not core.is_compiled_with_cuda(): + if use_device == DeviceType.CUDA and not core.is_compiled_with_cuda(): return img, label = self._init_data() @@ -167,11 +167,11 @@ class TestMNIST(TestParallelExecutorBase): np.mean(parallel_last_loss), single_last_loss, delta=1e-6) def test_simple_fc_parallel_accuracy(self): - self.check_simple_fc_parallel_accuracy(DeviceType.GPU) + self.check_simple_fc_parallel_accuracy(DeviceType.CUDA) self.check_simple_fc_parallel_accuracy(DeviceType.CPU) def check_batchnorm_fc_convergence(self, use_device, use_fast_executor): - if use_device == DeviceType.GPU and not core.is_compiled_with_cuda(): + if use_device == DeviceType.CUDA and not core.is_compiled_with_cuda(): return if use_device == DeviceType.XPU and not core.is_compiled_with_xpu(): return @@ -185,7 +185,7 @@ class TestMNIST(TestParallelExecutorBase): use_fast_executor=use_fast_executor) def test_batchnorm_fc(self): - for use_device in (DeviceType.CPU, DeviceType.GPU): + for use_device in (DeviceType.CPU, DeviceType.CUDA): for use_fast_executor in (False, True): self.check_batchnorm_fc_convergence(use_device, use_fast_executor) @@ -193,7 +193,7 @@ class TestMNIST(TestParallelExecutorBase): def test_batchnorm_fc_with_new_strategy(self): # NOTE: the computation result of nccl_reduce is non-deterministic, # related issue: https://github.com/NVIDIA/nccl/issues/157 - self._compare_reduce_and_allreduce(fc_with_batchnorm, DeviceType.GPU, + self._compare_reduce_and_allreduce(fc_with_batchnorm, DeviceType.CUDA, 1e-5, 1e-2) self._compare_reduce_and_allreduce(fc_with_batchnorm, DeviceType.CPU, 1e-5, 1e-2) diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor_pg.py b/python/paddle/fluid/tests/unittests/test_parallel_executor_pg.py index 45008c20827a85bd138626b52baa2c1fc6727922..e07b89f7aae765e54f06de2715ade910d4fe205f 100644 --- a/python/paddle/fluid/tests/unittests/test_parallel_executor_pg.py +++ b/python/paddle/fluid/tests/unittests/test_parallel_executor_pg.py @@ -32,7 +32,7 @@ class TestMNIST(TestParallelExecutorBase): # simple_fc def check_simple_fc_convergence(self, use_device, use_reduce=False): - if use_device == DeviceType.GPU and not core.is_compiled_with_cuda(): + if use_device == DeviceType.CUDA and not core.is_compiled_with_cuda(): return img, label = init_data() @@ -73,7 +73,7 @@ class TestMNIST(TestParallelExecutorBase): np.mean(parallel_last_loss), single_last_loss, delta=1e-6) def test_simple_fc_parallel_accuracy(self): - self.check_simple_fc_parallel_accuracy(DeviceType.GPU) + self.check_simple_fc_parallel_accuracy(DeviceType.CUDA) if __name__ == '__main__': diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_base_gpu.py b/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_base_gpu.py index ef6c3e118703f6c935dc4fa77705f397c832f25c..9d1364cc592fe20b9510da6c6f4b903b13cd6f23 100644 --- a/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_base_gpu.py +++ b/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_base_gpu.py @@ -30,7 +30,7 @@ class TestResnetGPU(TestResnetBase): optimizer=seresnext_net.optimizer, use_parallel_executor=False) self._compare_result_with_origin_model( - check_func, use_device=DeviceType.GPU, compare_seperately=False) + check_func, use_device=DeviceType.CUDA, compare_seperately=False) if __name__ == '__main__': diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_with_fuse_all_reduce_gpu.py b/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_with_fuse_all_reduce_gpu.py index 111ea507c37e19d7720729eecb1c67b4fb95fcf9..c747591c81622c70a59fdf128f8de0175bd01046 100644 --- a/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_with_fuse_all_reduce_gpu.py +++ b/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_with_fuse_all_reduce_gpu.py @@ -32,7 +32,7 @@ class TestResnetWithFuseAllReduceGPU(TestResnetBase): optimizer=seresnext_net.optimizer, fuse_all_reduce_ops=True) self._compare_result_with_origin_model( - check_func, use_device=DeviceType.GPU, delta2=1e-2) + check_func, use_device=DeviceType.CUDA, delta2=1e-2) if __name__ == '__main__': diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_with_reduce_cpu.py b/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_with_reduce_cpu.py index 2e5ab76377e6c25b5b078eaa6f5fdee495effee7..e67934d87f9577d7765e07806a10e68a47bf174f 100644 --- a/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_with_reduce_cpu.py +++ b/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_with_reduce_cpu.py @@ -21,7 +21,7 @@ import paddle.fluid.core as core class TestResnetWithReduceBase(TestParallelExecutorBase): def _compare_reduce_and_allreduce(self, use_device, delta2=1e-5): - if use_device == DeviceType.GPU and not core.is_compiled_with_cuda(): + if use_device == DeviceType.CUDA and not core.is_compiled_with_cuda(): return all_reduce_first_loss, all_reduce_last_loss = self.check_network_convergence( diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_with_reduce_gpu.py b/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_with_reduce_gpu.py index ff98d562c41697ba1630905507b810a0b4dfac00..4de1a6092dcae6976bf4e334788cfcc7d9b8f4ec 100644 --- a/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_with_reduce_gpu.py +++ b/python/paddle/fluid/tests/unittests/test_parallel_executor_seresnext_with_reduce_gpu.py @@ -20,7 +20,7 @@ from test_parallel_executor_seresnext_with_reduce_cpu import TestResnetWithReduc class TestResnetWithReduceGPU(TestResnetWithReduceBase): def test_seresnext_with_reduce(self): self._compare_reduce_and_allreduce( - use_device=DeviceType.GPU, delta2=1e-2) + use_device=DeviceType.CUDA, delta2=1e-2) if __name__ == '__main__': diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor_transformer.py b/python/paddle/fluid/tests/unittests/test_parallel_executor_transformer.py index 26036e41d9f46b7b7707f9fe83a754da05c1c999..1cb39eb131b826cf7f3d7459caedcb296968bf27 100644 --- a/python/paddle/fluid/tests/unittests/test_parallel_executor_transformer.py +++ b/python/paddle/fluid/tests/unittests/test_parallel_executor_transformer.py @@ -191,11 +191,11 @@ class TestTransformer(TestParallelExecutorBase): if core.is_compiled_with_cuda(): self.check_network_convergence( transformer, - use_device=DeviceType.GPU, + use_device=DeviceType.CUDA, feed_data_reader=get_feed_data_reader()) self.check_network_convergence( transformer, - use_device=DeviceType.GPU, + use_device=DeviceType.CUDA, enable_sequential_execution=True, feed_data_reader=get_feed_data_reader()) self.check_network_convergence(