diff --git a/paddle/fluid/operators/conditional_block_op.cc b/paddle/fluid/operators/conditional_block_op.cc index 8cc1d94260baccfe28d213b7e021956819e2e79e..580fde753816c30b188b8a99cc63fcbafde64e25 100644 --- a/paddle/fluid/operators/conditional_block_op.cc +++ b/paddle/fluid/operators/conditional_block_op.cc @@ -205,9 +205,10 @@ class ConditionalBlockGradInferShape : public framework::InferShapeBase { context->SetOutputsDim(framework::GradVarName("Params"), context->GetInputsDim("Params")); } - PADDLE_ENFORCE(context->HasOutputs(framework::GradVarName("X"))); - context->SetOutputsDim(framework::GradVarName("X"), - context->GetInputsDim("X")); + if (context->HasOutputs(framework::GradVarName("X"))) { + context->SetOutputsDim(framework::GradVarName("X"), + context->GetInputsDim("X")); + } } }; diff --git a/paddle/fluid/operators/merge_lod_tensor_op.cc b/paddle/fluid/operators/merge_lod_tensor_op.cc index a16861b3b77fc980ab932b9d88859b38ec36108b..2dc1467b0d4816d5cc0535eb62e936cf342a241c 100644 --- a/paddle/fluid/operators/merge_lod_tensor_op.cc +++ b/paddle/fluid/operators/merge_lod_tensor_op.cc @@ -44,8 +44,10 @@ class MergeLoDTensorOp : public framework::OperatorBase { scope.FindVar(Output("Out"))->GetMutable(); auto level = static_cast(Attr("level")); - auto &mask_dim = mask.dims(); + PADDLE_ENFORCE(in_true.numel() || in_false.numel(), + "Input(InTrue) or Input(InFalse) should be initialized."); + auto &mask_dim = mask.dims(); std::unique_ptr cpu_mask{new framework::LoDTensor()}; if (platform::is_cpu_place(mask.place())) { cpu_mask->ShareDataWith(mask); @@ -59,19 +61,27 @@ class MergeLoDTensorOp : public framework::OperatorBase { } auto *mask_data = cpu_mask->data(); - int rank = in_true.dims().size(); - platform::Place place = in_true.place(); - std::type_index data_type = in_true.type(); - framework::DDim in_true_dims = - framework::slice_ddim(in_true.dims(), 1, rank); - + platform::Place place = dev_place; int64_t batch_size = in_true.dims()[0] + in_false.dims()[0]; - auto in_true_dim_vec = framework::vectorize(in_true_dims); - in_true_dim_vec.insert(in_true_dim_vec.begin(), batch_size); + std::type_index data_type = + in_true.IsInitialized() ? in_true.type() : in_false.type(); + int rank; + framework::DDim in_dims; + if (in_true.IsInitialized()) { + rank = in_true.dims().size(); + in_dims = framework::slice_ddim(in_true.dims(), 1, rank); + } else { + rank = in_false.dims().size(); + in_dims = framework::slice_ddim(in_false.dims(), 1, rank); + } + + auto in_dim_vec = framework::vectorize(in_dims); + in_dim_vec.insert(in_dim_vec.begin(), batch_size); - framework::DDim out_dims = framework::make_ddim(in_true_dim_vec); + framework::DDim out_dims = framework::make_ddim(in_dim_vec); out->Resize(out_dims); + out->mutable_data(place, data_type); auto *out_lod = out->mutable_lod(); diff --git a/python/paddle/fluid/tests/test_mnist_if_else_op.py b/python/paddle/fluid/tests/test_if_else_op.py similarity index 66% rename from python/paddle/fluid/tests/test_mnist_if_else_op.py rename to python/paddle/fluid/tests/test_if_else_op.py index d34f52db5ffc889f17513d034ad2c99f696b0cdf..1b58925599de62510ea9048f5210bb0b7e49f933 100644 --- a/python/paddle/fluid/tests/test_mnist_if_else_op.py +++ b/python/paddle/fluid/tests/test_if_else_op.py @@ -14,10 +14,11 @@ import paddle import paddle.fluid.layers as layers -from paddle.fluid.framework import Program, program_guard, default_main_program, default_startup_program +from paddle.fluid.framework import Program, program_guard from paddle.fluid.executor import Executor from paddle.fluid.optimizer import MomentumOptimizer import paddle.fluid.core as core +import paddle.fluid as fluid import unittest import numpy as np @@ -31,14 +32,13 @@ class TestMNISTIfElseOp(unittest.TestCase): label = layers.data(name='y', shape=[1], dtype='int64') - limit = layers.fill_constant_batch_size_like( - input=label, dtype='int64', shape=[1], value=5.0) + limit = layers.fill_constant(shape=[1], dtype='int64', value=5) cond = layers.less_than(x=label, y=limit) true_image, false_image = layers.split_lod_tensor( input=image, mask=cond) true_out = layers.create_tensor(dtype='float32') - true_cond = layers.ConditionalBlock([true_image]) + true_cond = layers.ConditionalBlock([cond]) with true_cond.block(): hidden = layers.fc(input=true_image, size=100, act='tanh') @@ -46,7 +46,7 @@ class TestMNISTIfElseOp(unittest.TestCase): layers.assign(input=prob, output=true_out) false_out = layers.create_tensor(dtype='float32') - false_cond = layers.ConditionalBlock([false_image]) + false_cond = layers.ConditionalBlock([cond]) with false_cond.block(): hidden = layers.fc(input=false_image, size=200, act='tanh') @@ -64,7 +64,7 @@ class TestMNISTIfElseOp(unittest.TestCase): train_reader = paddle.batch( paddle.reader.shuffle( paddle.dataset.mnist.train(), buf_size=8192), - batch_size=200) + batch_size=10) place = core.CPUPlace() exe = Executor(place) @@ -94,8 +94,7 @@ class TestMNISTIfElseOp(unittest.TestCase): label = layers.data(name='y', shape=[1], dtype='int64') - limit = layers.fill_constant_batch_size_like( - input=label, dtype='int64', shape=[1], value=5.0) + limit = layers.fill_constant(shape=[1], dtype='int64', value=5) cond = layers.less_than(x=label, y=limit) ie = layers.IfElse(cond) @@ -125,7 +124,7 @@ class TestMNISTIfElseOp(unittest.TestCase): place = core.CPUPlace() exe = Executor(place) - exe.run(kwargs['startup_program']) + exe.run(startup_prog) PASS_NUM = 100 for pass_id in range(PASS_NUM): for data in train_reader(): @@ -133,7 +132,7 @@ class TestMNISTIfElseOp(unittest.TestCase): y_data = np.array(map(lambda x: x[1], data)).astype("int64") y_data = y_data.reshape((y_data.shape[0], 1)) - outs = exe.run(kwargs['main_program'], + outs = exe.run(prog, feed={'x': x_data, 'y': y_data}, fetch_list=[avg_loss]) @@ -143,6 +142,67 @@ class TestMNISTIfElseOp(unittest.TestCase): self.assertFalse(True) +class TestIfElse(unittest.TestCase): + def set_test_case(self): + # condiction is: self.data < self.cond_value + self.cond_value = 0.5 + self.data = np.random.rand(25, 1).astype(np.float32) + + def compare_ifelse_op_and_numpy(self, place): + self.set_test_case() + + prog = Program() + startup_prog = Program() + with program_guard(prog, startup_prog): + src = layers.data(name='data', shape=[1], dtype='float32') + cond = layers.fill_constant( + [1], dtype='float32', value=self.cond_value) + ifcond = layers.less_than(x=src, y=cond) + ie = layers.IfElse(ifcond) + with ie.true_block(): + true_target = ie.input(src) + ie.output(true_target) + + with ie.false_block(): + false_target = ie.input(src) + ie.output(false_target) + if_out = ie() + out = layers.reduce_sum(if_out) + + exe = fluid.Executor(place) + exe.run(fluid.default_startup_program()) + fetch_list = [out] + o1, = exe.run(fluid.default_main_program(), + feed={'data': self.data}, + fetch_list=[out]) + o2 = np.sum(self.data) + self.assertTrue( + np.allclose( + o1, o2, atol=1e-8), + "IfElse result : " + str(o1) + "\n Numpy result :" + str(o2)) + + def test_cpu(self): + self.compare_ifelse_op_and_numpy(fluid.CPUPlace()) + + def test_cuda(self): + if not core.is_compiled_with_cuda(): + return + self.compare_ifelse_op_and_numpy(fluid.CUDAPlace(0)) + + +class TestIfElseTrueBranch(TestIfElse): + def set_test_case(self): + # condiction is: self.data < self.cond_value + self.cond_value = 10. + self.data = np.random.rand(25, 1).astype(np.float32) + + +class TestIfElseFalseBranch(TestIfElse): + def set_test_case(self): + # condiction is: self.data < self.cond_value + self.cond_value = -10. + self.data = np.random.rand(25, 1).astype(np.float32) + + if __name__ == '__main__': - # temp disable if else unittest since it could be buggy. - exit(0) + unittest.main()