diff --git a/paddle/fluid/operators/fill_constant_op.cc b/paddle/fluid/operators/fill_constant_op.cc index 130f18dde4f979a6a9925ede9cbf745fcec14d48..2826b82117db113d4d8c10095e89f610ca895775 100644 --- a/paddle/fluid/operators/fill_constant_op.cc +++ b/paddle/fluid/operators/fill_constant_op.cc @@ -15,7 +15,6 @@ limitations under the License. */ #include "paddle/fluid/framework/data_type.h" #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/operators/math/math_function.h" -#include "paddle/fluid/platform/device_context.h" namespace paddle { namespace operators { @@ -41,19 +40,33 @@ class FillConstantOp : public framework::OperatorBase { static_cast(Attr("dtype")); auto value = Attr("value"); auto force_cpu = Attr("force_cpu"); - auto &out = - *scope.FindVar(Output("Out"))->GetMutable(); - out.Resize(framework::make_ddim(Attr>("shape"))); + + framework::Tensor *tensor = nullptr; + + auto &out_var = *scope.FindVar(Output("Out")); + + if (out_var.IsType()) { + tensor = out_var.GetMutable(); + tensor->Resize(framework::make_ddim(Attr>("shape"))); + } else if (out_var.IsType()) { + tensor = out_var.GetMutable()->mutable_value(); + tensor->Resize(framework::make_ddim(Attr>("shape"))); + } else { + PADDLE_THROW( + "fill constant op's output only" + "supports SelectedRows and LoDTensor"); + } + if (force_cpu) { auto cpu = platform::CPUPlace(); - out.mutable_data(cpu, framework::ToTypeIndex(data_type)); + tensor->mutable_data(cpu, framework::ToTypeIndex(data_type)); } else { - out.mutable_data(dev_place, framework::ToTypeIndex(data_type)); + tensor->mutable_data(dev_place, framework::ToTypeIndex(data_type)); } platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance(); auto &dev_ctx = *pool.Get(dev_place); - math::set_constant(dev_ctx, &out, value); + math::set_constant(dev_ctx, tensor, value); } }; diff --git a/paddle/fluid/operators/uniform_random_op.cc b/paddle/fluid/operators/uniform_random_op.cc index 5248767c2eeb9388c26d203e64f8b2c68ffe0865..763bb403588d13c15271d26b09813dddf3a5dd8c 100644 --- a/paddle/fluid/operators/uniform_random_op.cc +++ b/paddle/fluid/operators/uniform_random_op.cc @@ -37,7 +37,7 @@ class CPUUniformRandomKernel : public framework::OpKernel { } else { PADDLE_THROW( "uniform_random_op's output only" - "supports SelectedRows and Tensor"); + "supports SelectedRows and LoDTensor"); } T* data = tensor->mutable_data(ctx.GetPlace()); unsigned int seed = static_cast(ctx.Attr("seed")); diff --git a/paddle/fluid/operators/uniform_random_op.cu b/paddle/fluid/operators/uniform_random_op.cu index e1c7323a30233f4ec4f60e46aa6088ee6d8601b7..bbb692b0ddfc18e8a62c0d2a6bac88f9932f6704 100644 --- a/paddle/fluid/operators/uniform_random_op.cu +++ b/paddle/fluid/operators/uniform_random_op.cu @@ -54,7 +54,7 @@ class GPUUniformRandomKernel : public framework::OpKernel { } else { PADDLE_THROW( "uniform_random_op's output only" - "supports SelectedRows and Tensor"); + "supports SelectedRows and LoDTensor"); } T* data = tensor->mutable_data(context.GetPlace()); unsigned int seed = static_cast(context.Attr("seed")); diff --git a/python/paddle/fluid/tests/unittests/dist_simnet_bow.py b/python/paddle/fluid/tests/unittests/dist_simnet_bow.py index 59fca7073511ea45e790b549515db2b67df6212a..5c2341a2d185fdca3783683596b5db12fc151767 100644 --- a/python/paddle/fluid/tests/unittests/dist_simnet_bow.py +++ b/python/paddle/fluid/tests/unittests/dist_simnet_bow.py @@ -91,16 +91,21 @@ def train_network(batch_size, is_distributed=False, is_sparse=False): is_distributed=is_distributed, size=[dict_dim, emb_dim], param_attr=fluid.ParamAttr( - name="__emb__", learning_rate=emb_lr), + initializer=fluid.initializer.Constant(value=0.01), + name="__emb__", + learning_rate=emb_lr), is_sparse=is_sparse) ## vsum q_sum = fluid.layers.sequence_pool(input=q_emb, pool_type='sum') q_ss = fluid.layers.softsign(q_sum) ## fc layer after conv - q_fc = fluid.layers.fc(input=q_ss, - size=hid_dim, - param_attr=fluid.ParamAttr( - name="__q_fc__", learning_rate=base_lr)) + q_fc = fluid.layers.fc( + input=q_ss, + size=hid_dim, + param_attr=fluid.ParamAttr( + initializer=fluid.initializer.Constant(value=0.01), + name="__q_fc__", + learning_rate=base_lr)) # label data label = fluid.layers.data(name="label", shape=[1], dtype="int64") # pt @@ -112,17 +117,22 @@ def train_network(batch_size, is_distributed=False, is_sparse=False): is_distributed=is_distributed, size=[dict_dim, emb_dim], param_attr=fluid.ParamAttr( - name="__emb__", learning_rate=emb_lr), + initializer=fluid.initializer.Constant(value=0.01), + name="__emb__", + learning_rate=emb_lr), is_sparse=is_sparse) ## vsum pt_sum = fluid.layers.sequence_pool(input=pt_emb, pool_type='sum') pt_ss = fluid.layers.softsign(pt_sum) ## fc layer - pt_fc = fluid.layers.fc(input=pt_ss, - size=hid_dim, - param_attr=fluid.ParamAttr( - name="__fc__", learning_rate=base_lr), - bias_attr=fluid.ParamAttr(name="__fc_b__")) + pt_fc = fluid.layers.fc( + input=pt_ss, + size=hid_dim, + param_attr=fluid.ParamAttr( + initializer=fluid.initializer.Constant(value=0.01), + name="__fc__", + learning_rate=base_lr), + bias_attr=fluid.ParamAttr(name="__fc_b__")) # nt nt = fluid.layers.data( name="neg_title_ids", shape=[1], dtype="int64", lod_level=1) @@ -132,17 +142,22 @@ def train_network(batch_size, is_distributed=False, is_sparse=False): is_distributed=is_distributed, size=[dict_dim, emb_dim], param_attr=fluid.ParamAttr( - name="__emb__", learning_rate=emb_lr), + initializer=fluid.initializer.Constant(value=0.01), + name="__emb__", + learning_rate=emb_lr), is_sparse=is_sparse) ## vsum nt_sum = fluid.layers.sequence_pool(input=nt_emb, pool_type='sum') nt_ss = fluid.layers.softsign(nt_sum) ## fc layer - nt_fc = fluid.layers.fc(input=nt_ss, - size=hid_dim, - param_attr=fluid.ParamAttr( - name="__fc__", learning_rate=base_lr), - bias_attr=fluid.ParamAttr(name="__fc_b__")) + nt_fc = fluid.layers.fc( + input=nt_ss, + size=hid_dim, + param_attr=fluid.ParamAttr( + initializer=fluid.initializer.Constant(value=0.01), + name="__fc__", + learning_rate=base_lr), + bias_attr=fluid.ParamAttr(name="__fc_b__")) cos_q_pt = fluid.layers.cos_sim(q_fc, pt_fc) cos_q_nt = fluid.layers.cos_sim(q_fc, nt_fc) # loss @@ -163,7 +178,6 @@ def get_one_data(file_list): with open(file, "r") as fin: for i in fin: contents.append(i.strip()) - random.shuffle(contents) for index, q in enumerate(contents): try: one_data = [[int(j) for j in i.split(" ")] @@ -205,7 +219,8 @@ def get_train_reader(batch_size): class TestDistSimnetBow2x2(TestDistRunnerBase): def get_model(self, batch_size=2): # Train program - avg_cost, acc, predict = train_network(batch_size, False, False) + avg_cost, acc, predict = \ + train_network(batch_size, bool(int(os.environ["IS_DISTRIBUTED"])), bool(int(os.environ["IS_SPARSE"]))) inference_program = fluid.default_main_program().clone() @@ -219,7 +234,15 @@ class TestDistSimnetBow2x2(TestDistRunnerBase): if __name__ == "__main__": + paddle.dataset.common.download(DATA_URL, 'simnet', DATA_MD5, "train") + import os os.environ['CPU_NUM'] = '1' - paddle.dataset.common.download(DATA_URL, 'simnet', DATA_MD5, "train") + + os.environ["IS_DISTRIBUTED"] = '0' + os.environ["IS_SPARSE"] = '0' runtime_main(TestDistSimnetBow2x2) + +# os.environ["IS_DISTRIBUTED"] = '0' +# os.environ["IS_SPARSE"] = '1' +# runtime_main(TestDistSimnetBow2x2) diff --git a/python/paddle/fluid/tests/unittests/test_dist_base.py b/python/paddle/fluid/tests/unittests/test_dist_base.py index 0e815c91446b285ba2c2c5aa9ad18d97f51eae65..d05fd508c57a8e9eba4cbb503b919a4a69aecdfe 100644 --- a/python/paddle/fluid/tests/unittests/test_dist_base.py +++ b/python/paddle/fluid/tests/unittests/test_dist_base.py @@ -155,7 +155,7 @@ class TestDistBase(unittest.TestCase): self._sync_mode = True self._setup_config() - def start_pserver(self, model_file, check_error_log): + def start_pserver(self, model_file, check_error_log, required_envs): sync_mode_str = "TRUE" if self._sync_mode else "FALSE" ps0_ep, ps1_ep = self._ps_endpoints.split(",") ps0_cmd = "%s %s pserver %s 0 %s %d TRUE %s" % \ @@ -168,15 +168,23 @@ class TestDistBase(unittest.TestCase): ps0_pipe = subprocess.PIPE ps1_pipe = subprocess.PIPE if check_error_log: + required_envs["GLOG_v"] = "7" + required_envs["GLOG_logtostderr"] = "1" print("ps0_cmd:", ps0_cmd) print("ps1_cmd:", ps1_cmd) ps0_pipe = open("/tmp/ps0_err.log", "wb") ps1_pipe = open("/tmp/ps1_err.log", "wb") ps0_proc = subprocess.Popen( - ps0_cmd.split(" "), stdout=subprocess.PIPE, stderr=ps0_pipe) + ps0_cmd.split(" "), + stdout=subprocess.PIPE, + stderr=ps0_pipe, + env=required_envs) ps1_proc = subprocess.Popen( - ps1_cmd.split(" "), stdout=subprocess.PIPE, stderr=ps1_pipe) + ps1_cmd.split(" "), + stdout=subprocess.PIPE, + stderr=ps1_pipe, + env=required_envs) if not check_error_log: return ps0_proc, ps1_proc, None, None