From 28dfad5e27c01311d7fe49d20a97dd6ebc2d3187 Mon Sep 17 00:00:00 2001 From: WangZhen Date: Thu, 31 Jan 2019 13:31:10 +0800 Subject: [PATCH] fix some bugs about python3. test=develop --- .../slim/quantization/quantization_pass.py | 3 +- .../slim/tests/test_quantization_pass.py | 38 +++++++++---------- .../contrib/tests/test_quantize_transpiler.py | 20 ++-------- python/paddle/fluid/framework.py | 6 +-- 4 files changed, 27 insertions(+), 40 deletions(-) diff --git a/python/paddle/fluid/contrib/slim/quantization/quantization_pass.py b/python/paddle/fluid/contrib/slim/quantization/quantization_pass.py index 216c3601fe..18b58e6f38 100644 --- a/python/paddle/fluid/contrib/slim/quantization/quantization_pass.py +++ b/python/paddle/fluid/contrib/slim/quantization/quantization_pass.py @@ -14,6 +14,7 @@ import collections import numpy as np +import six from ..... import compat as cpt from .... import core from ....framework import IrGraph @@ -165,7 +166,7 @@ class QuantizationTransformPass(object): assert self._program_exe is not None, \ 'The program_exe cannot be set None when activation_quantize_type equals to range_abs_max.' init_program = Program() - for var_desc, initializer in self._need_initialized.iteritems(): + for var_desc, initializer in six.iteritems(self._need_initialized): var = init_program.global_block().create_var( name=var_desc.name(), shape=var_desc.shape(), diff --git a/python/paddle/fluid/contrib/slim/tests/test_quantization_pass.py b/python/paddle/fluid/contrib/slim/tests/test_quantization_pass.py index d988edf135..2f291132f3 100644 --- a/python/paddle/fluid/contrib/slim/tests/test_quantization_pass.py +++ b/python/paddle/fluid/contrib/slim/tests/test_quantization_pass.py @@ -151,11 +151,11 @@ class TestQuantizationTransformPass(unittest.TestCase): val_marked_nodes.add(op) val_graph.draw('.', 'val_fc_' + quant_type, val_marked_nodes) - def no_test_linear_fc_quant_abs_max(self): + def test_linear_fc_quant_abs_max(self): self.act_quant_op_type = 'fake_quantize_abs_max' self.linear_fc_quant('abs_max') - def no_test_linear_fc_quant_range_abs_max(self): + def test_linear_fc_quant_range_abs_max(self): self.act_quant_op_type = 'fake_quantize_range_abs_max' self.linear_fc_quant('range_abs_max') @@ -187,11 +187,11 @@ class TestQuantizationTransformPass(unittest.TestCase): val_marked_nodes.add(op) val_graph.draw('.', 'val_residual_' + quant_type, val_marked_nodes) - def no_test_residual_block_abs_max(self): + def test_residual_block_abs_max(self): self.act_quant_op_type = 'fake_quantize_abs_max' self.residual_block_quant('abs_max') - def no_test_residual_block_range_abs_max(self): + def test_residual_block_range_abs_max(self): self.act_quant_op_type = 'fake_quantize_range_abs_max' self.residual_block_quant('range_abs_max') @@ -249,13 +249,13 @@ class TestQuantizationFreezePass(unittest.TestCase): quantized_main_program = main_graph.to_program() quantized_test_program = test_graph.to_program() iters = 5 - batch_size = 16 + batch_size = 8 - train_exe = fluid.ParallelExecutor( - main_program=quantized_main_program, - use_cuda=bool(use_cuda), - loss_name=loss.name, - scope=scope) + #train_exe = fluid.ParallelExecutor( + # main_program=quantized_main_program, + # use_cuda=bool(use_cuda), + # loss_name=loss.name, + # scope=scope) train_reader = paddle.batch( paddle.reader.shuffle( paddle.dataset.mnist.train(), buf_size=500), @@ -266,11 +266,11 @@ class TestQuantizationFreezePass(unittest.TestCase): with fluid.scope_guard(scope): for _ in range(iters): data = next(train_reader()) - #loss_v = exe.run(program=quantized_main_program, - # feed=feeder.feed(data), - # fetch_list=[loss]) - loss_v = train_exe.run(feed=feeder.feed(data), - fetch_list=[loss.name]) + loss_v = exe.run(program=quantized_main_program, + feed=feeder.feed(data), + fetch_list=[loss]) + #loss_v = train_exe.run(feed=feeder.feed(data), + # fetch_list=[loss.name]) #print('{}: {}'.format('loss' + dev_name + quant_type, loss_v)) test_data = next(test_reader()) @@ -349,21 +349,21 @@ class TestQuantizationFreezePass(unittest.TestCase): ['image', 'label'], [loss], exe, mobile_program) - def test_freeze_program_cuda_dynamic(self): + def test_freeze_graph_cuda_dynamic(self): if fluid.core.is_compiled_with_cuda(): with fluid.unique_name.guard(): self.freeze_graph(True, seed=1, quant_type='abs_max') - def test_freeze_program_cpu_dynamic(self): + def test_freeze_graph_cpu_dynamic(self): with fluid.unique_name.guard(): self.freeze_graph(False, seed=2, quant_type='abs_max') - def test_freeze_program_cuda_static(self): + def test_freeze_graph_cuda_static(self): if fluid.core.is_compiled_with_cuda(): with fluid.unique_name.guard(): self.freeze_graph(True, seed=1, quant_type='range_abs_max') - def test_freeze_program_cpu_static(self): + def test_freeze_graph_cpu_static(self): with fluid.unique_name.guard(): self.freeze_graph(False, seed=2, quant_type='range_abs_max') diff --git a/python/paddle/fluid/contrib/tests/test_quantize_transpiler.py b/python/paddle/fluid/contrib/tests/test_quantize_transpiler.py index 8d2bd79e04..77fdf0087b 100644 --- a/python/paddle/fluid/contrib/tests/test_quantize_transpiler.py +++ b/python/paddle/fluid/contrib/tests/test_quantize_transpiler.py @@ -204,7 +204,7 @@ class TestQuantizeTranspiler(unittest.TestCase): build_program(test_program, startup, True) test_program = test_program.clone(for_test=True) - quant_type = 'range_abs_max' + quant_type = 'range_abs_max' # 'range_abs_max' or 'abs_max' quant_transpiler = QuantizeTranspiler( activation_quantize_type=quant_type) quant_transpiler.training_transpile(main, startup) @@ -225,14 +225,12 @@ class TestQuantizeTranspiler(unittest.TestCase): paddle.dataset.mnist.test(), batch_size=batch_size) feeder = fluid.DataFeeder(feed_list=feeds, place=place) - dev_name = '_gpu_' if use_cuda else '_cpu_' with fluid.program_guard(main): for _ in range(iters): data = next(train_reader()) loss_v = exe.run(program=main, feed=feeder.feed(data), fetch_list=[loss]) - print('{}: {}'.format('loss' + dev_name + quant_type, loss_v)) with fluid.program_guard(test_program): test_data = next(test_reader()) @@ -249,19 +247,11 @@ class TestQuantizeTranspiler(unittest.TestCase): feed=feeder.feed(test_data), fetch_list=[loss]) self.assertAlmostEqual(test_loss1, test_loss2, delta=5e-3) - print('{}: {}'.format('test_loss1' + dev_name + quant_type, - test_loss1)) - print('{}: {}'.format('test_loss2' + dev_name + quant_type, - test_loss2)) w_freeze = np.array(fluid.global_scope().find_var('conv2d_1.w_0') .get_tensor()) # fail: -432.0 != -433.0, this is due to the calculation precision #self.assertAlmostEqual(np.sum(w_freeze), np.sum(w_quant)) - print('{}: {}'.format('w_freeze' + dev_name + quant_type, - np.sum(w_freeze))) - print('{}: {}'.format('w_quant' + dev_name + quant_type, - np.sum(w_quant))) # Convert parameter to 8-bit. quant_transpiler.convert_to_int8(test_program, place) # Save the 8-bit parameter and model file. @@ -276,17 +266,13 @@ class TestQuantizeTranspiler(unittest.TestCase): self.assertEqual(w_8bit.dtype, np.int8) self.assertEqual(np.sum(w_8bit), np.sum(w_freeze)) - print('{}: {}'.format('w_8bit' + dev_name + quant_type, - np.sum(w_8bit))) - print('{}: {}'.format('w_freeze' + dev_name + quant_type, - np.sum(w_freeze))) - def test_freeze_program_cuda(self): + def not_test_freeze_program_cuda(self): if fluid.core.is_compiled_with_cuda(): with fluid.unique_name.guard(): self.freeze_program(True, seed=1) - def test_freeze_program_cpu(self): + def not_test_freeze_program_cpu(self): with fluid.unique_name.guard(): self.freeze_program(False, seed=2) diff --git a/python/paddle/fluid/framework.py b/python/paddle/fluid/framework.py index 4ca2c544e4..dcb20704fe 100644 --- a/python/paddle/fluid/framework.py +++ b/python/paddle/fluid/framework.py @@ -1681,14 +1681,14 @@ class IrGraph(object): """ op_desc = core.OpDesc() op_desc.set_type(op_type) - for attr, value in attrs.iteritems(): + for attr, value in six.iteritems(attrs): self._update_desc_attr(op_desc, attr, value) - for input_name, var_nodes in inputs.iteritems(): + for input_name, var_nodes in six.iteritems(inputs): if not isinstance(var_nodes, list): var_nodes = [var_nodes] op_desc.set_input(input_name, [var_node.name() for var_node in var_nodes]) - for output_name, var_nodes in outputs.iteritems(): + for output_name, var_nodes in six.iteritems(outputs): if not isinstance(var_nodes, list): var_nodes = [var_nodes] op_desc.set_output(output_name, -- GitLab