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 11da3520035784ca2cfa249f0a99f982a06442e5..3b82380f9433d4efc1e2a314165ed14e7bd6fdcb 100644 --- a/python/paddle/fluid/contrib/slim/tests/test_quantization_pass.py +++ b/python/paddle/fluid/contrib/slim/tests/test_quantization_pass.py @@ -123,7 +123,7 @@ class TestQuantizationTransformPass(unittest.TestCase): arg_name.endswith('.quantized.dequantized')) self.assertTrue(arg_name in quantized_ops) - def linear_fc_quant(self, quant_type, enable_ce=False): + def linear_fc_quant(self, quant_type, for_ci=False): main = fluid.Program() startup = fluid.Program() with fluid.program_guard(main, startup): @@ -138,7 +138,7 @@ class TestQuantizationTransformPass(unittest.TestCase): place=place, activation_quantize_type=quant_type) transform_pass.apply(graph) - if not enable_ce: + if not for_ci: marked_nodes = set() for op in graph.all_op_nodes(): if op.name().find('quantize') > -1: @@ -147,7 +147,7 @@ class TestQuantizationTransformPass(unittest.TestCase): program = graph.to_program() self.check_program(transform_pass, program) val_graph = IrGraph(core.Graph(program.desc), for_test=False) - if not enable_ce: + if not for_ci: val_marked_nodes = set() for op in val_graph.all_op_nodes(): if op.name().find('quantize') > -1: @@ -155,12 +155,12 @@ class TestQuantizationTransformPass(unittest.TestCase): val_graph.draw('.', 'val_fc_' + quant_type, val_marked_nodes) def test_linear_fc_quant_abs_max(self): - self.linear_fc_quant('abs_max', enable_ce=True) + self.linear_fc_quant('abs_max', for_ci=True) def test_linear_fc_quant_range_abs_max(self): - self.linear_fc_quant('range_abs_max', enable_ce=True) + self.linear_fc_quant('range_abs_max', for_ci=True) - def residual_block_quant(self, quant_type, enable_ce=False): + def residual_block_quant(self, quant_type, for_ci=False): main = fluid.Program() startup = fluid.Program() with fluid.program_guard(main, startup): @@ -175,7 +175,7 @@ class TestQuantizationTransformPass(unittest.TestCase): place=place, activation_quantize_type=quant_type) transform_pass.apply(graph) - if not enable_ce: + if not for_ci: marked_nodes = set() for op in graph.all_op_nodes(): if op.name().find('quantize') > -1: @@ -184,7 +184,7 @@ class TestQuantizationTransformPass(unittest.TestCase): program = graph.to_program() self.check_program(transform_pass, program) val_graph = IrGraph(core.Graph(program.desc), for_test=False) - if not enable_ce: + if not for_ci: val_marked_nodes = set() for op in val_graph.all_op_nodes(): if op.name().find('quantize') > -1: @@ -192,14 +192,14 @@ class TestQuantizationTransformPass(unittest.TestCase): val_graph.draw('.', 'val_residual_' + quant_type, val_marked_nodes) def test_residual_block_abs_max(self): - self.residual_block_quant('abs_max', enable_ce=True) + self.residual_block_quant('abs_max', for_ci=True) def test_residual_block_range_abs_max(self): - self.residual_block_quant('range_abs_max', enable_ce=True) + self.residual_block_quant('range_abs_max', for_ci=True) class TestQuantizationFreezePass(unittest.TestCase): - def freeze_graph(self, use_cuda, seed, quant_type, enable_ce=False): + def freeze_graph(self, use_cuda, seed, quant_type, for_ci=False): def build_program(main, startup, is_test): main.random_seed = seed startup.random_seed = seed @@ -237,7 +237,7 @@ class TestQuantizationFreezePass(unittest.TestCase): transform_pass.apply(main_graph) transform_pass.apply(test_graph) dev_name = '_gpu_' if use_cuda else '_cpu_' - if not enable_ce: + if not for_ci: marked_nodes = set() for op in main_graph.all_op_nodes(): if op.name().find('quantize') > -1: @@ -267,7 +267,7 @@ class TestQuantizationFreezePass(unittest.TestCase): loss_v = exe.run(program=quantized_main_program, feed=feeder.feed(data), fetch_list=[loss]) - if not enable_ce: + if not for_ci: print('{}: {}'.format('loss' + dev_name + quant_type, loss_v)) @@ -284,7 +284,7 @@ class TestQuantizationFreezePass(unittest.TestCase): # Freeze graph for inference, but the weight of fc/conv is still float type. freeze_pass = QuantizationFreezePass(scope=scope, place=place) freeze_pass.apply(test_graph) - if not enable_ce: + if not for_ci: marked_nodes = set() for op in test_graph.all_op_nodes(): if op.name().find('quantize') > -1: @@ -298,7 +298,7 @@ class TestQuantizationFreezePass(unittest.TestCase): feed=feeder.feed(test_data), fetch_list=[loss]) self.assertAlmostEqual(test_loss1, test_loss2, delta=5e-3) - if not enable_ce: + if not for_ci: print('{}: {}'.format('test_loss1' + dev_name + quant_type, test_loss1)) print('{}: {}'.format('test_loss2' + dev_name + quant_type, @@ -306,7 +306,7 @@ class TestQuantizationFreezePass(unittest.TestCase): w_freeze = np.array(scope.find_var('conv2d_1.w_0').get_tensor()) # Maybe failed, this is due to the calculation precision # self.assertAlmostEqual(np.sum(w_freeze), np.sum(w_quant)) - if not enable_ce: + if not for_ci: print('{}: {}'.format('w_freeze' + dev_name + quant_type, np.sum(w_freeze))) print('{}: {}'.format('w_quant' + dev_name + quant_type, @@ -315,7 +315,7 @@ class TestQuantizationFreezePass(unittest.TestCase): # Convert parameter to 8-bit. convert_int8_pass = ConvertToInt8Pass(scope=scope, place=place) convert_int8_pass.apply(test_graph) - if not enable_ce: + if not for_ci: marked_nodes = set() for op in test_graph.all_op_nodes(): if op.name().find('quantize') > -1: @@ -335,7 +335,7 @@ class TestQuantizationFreezePass(unittest.TestCase): w_8bit = np.array(scope.find_var('conv2d_1.w_0.int8').get_tensor()) self.assertEqual(w_8bit.dtype, np.int8) self.assertEqual(np.sum(w_8bit), np.sum(w_freeze)) - if not enable_ce: + if not for_ci: print('{}: {}'.format('w_8bit' + dev_name + quant_type, np.sum(w_8bit))) print('{}: {}'.format('w_freeze' + dev_name + quant_type, @@ -343,7 +343,7 @@ class TestQuantizationFreezePass(unittest.TestCase): mobile_pass = TransformForMobilePass() mobile_pass.apply(test_graph) - if not enable_ce: + if not for_ci: marked_nodes = set() for op in test_graph.all_op_nodes(): if op.name().find('quantize') > -1: @@ -361,23 +361,22 @@ class TestQuantizationFreezePass(unittest.TestCase): if fluid.core.is_compiled_with_cuda(): with fluid.unique_name.guard(): self.freeze_graph( - True, seed=1, quant_type='abs_max', enable_ce=True) + True, seed=1, quant_type='abs_max', for_ci=True) def test_freeze_graph_cpu_dynamic(self): with fluid.unique_name.guard(): - self.freeze_graph( - False, seed=2, quant_type='abs_max', enable_ce=True) + self.freeze_graph(False, seed=2, quant_type='abs_max', for_ci=True) 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', enable_ce=True) + True, seed=1, quant_type='range_abs_max', for_ci=True) def test_freeze_graph_cpu_static(self): with fluid.unique_name.guard(): self.freeze_graph( - False, seed=2, quant_type='range_abs_max', enable_ce=True) + False, seed=2, quant_type='range_abs_max', for_ci=True) if __name__ == '__main__':