diff --git a/python/paddle/v2/fluid/framework.py b/python/paddle/v2/fluid/framework.py index a12427258e9d3142abcb84249a10dabd8e96b792..a517db68c5886fbcbe19e6981aee5bf3971352e4 100644 --- a/python/paddle/v2/fluid/framework.py +++ b/python/paddle/v2/fluid/framework.py @@ -740,6 +740,9 @@ class Block(object): raise e self.desc.remove_op(start, end + 1) + def slice_ops(self, start, end): + return list(self.ops)[start:end] + def prepend_op(self, *args, **kwargs): op_desc = self.desc.prepend_op() op = Operator(self, op_desc, *args, **kwargs) diff --git a/python/paddle/v2/fluid/optimizer.py b/python/paddle/v2/fluid/optimizer.py index 7844a4e2df1ce3989e48082f6472292560fbf1ee..f8a00e3a5fb4038a97a951a01c3a2f1a4488ae75 100644 --- a/python/paddle/v2/fluid/optimizer.py +++ b/python/paddle/v2/fluid/optimizer.py @@ -190,6 +190,8 @@ class Optimizer(object): # Create any accumulators program = loss.block.program with program_guard(program, startup_program): + global_block = framework.default_main_program().global_block() + start = len(global_block.ops) self.helper = LayerHelper(self.__class__.__name__) self._create_accumulators(loss.block, [p[0] for p in parameters_and_grads]) @@ -203,19 +205,14 @@ class Optimizer(object): param_and_grad) optimize_ops.append(optimize_op) - # Returned list of ops can include more ops in addition - # to optimization ops - return_ops = optimize_ops - # Get custom finish ops for subclasses # FIXME: Need to fix this once we figure out how to handle dependencies - finish_ops = self._finish_update(loss.block) - if finish_ops is not None: - return_ops += finish_ops + self._finish_update(loss.block) if self._global_step is not None: - return_ops.append(self._increment_global_step(loss.block)) - return return_ops + self._increment_global_step(loss.block) + end = len(global_block.ops) + return global_block.slice_ops(start, end) def minimize(self, loss, diff --git a/python/paddle/v2/fluid/tests/test_optimizer.py b/python/paddle/v2/fluid/tests/test_optimizer.py index 480ee7091579ba171ca957cb4d25f0034e0534c0..dc6b84dcdc04dd185d97c3cc4b9f00305a911efb 100644 --- a/python/paddle/v2/fluid/tests/test_optimizer.py +++ b/python/paddle/v2/fluid/tests/test_optimizer.py @@ -42,9 +42,9 @@ class TestOptimizer(unittest.TestCase): type="mean", inputs={"X": mul_out}, outputs={"Out": mean_out}) sgd_optimizer = optimizer.SGDOptimizer(learning_rate=0.01) opts, _ = sgd_optimizer.minimize(mean_out, init_program) - self.assertEqual(len(opts), 1) - sgd_op = opts[0] - self.assertEqual(sgd_op.type, "sgd") + self.assertEqual(len(opts), 3) + self.assertEqual([op.type for op in opts], + ["fill_constant", "elementwise_mul", "sgd"]) def test_sgd_optimizer_with_global_step(self): init_program = framework.Program() @@ -72,11 +72,10 @@ class TestOptimizer(unittest.TestCase): sgd_optimizer = optimizer.SGDOptimizer( learning_rate=learning_rate, global_step=global_step) opts, _ = sgd_optimizer.minimize(mean_out, init_program) - self.assertEqual(len(opts), 2) - sgd_op = opts[0] - self.assertEqual(sgd_op.type, "sgd") - increment_op = opts[1] - self.assertEqual(increment_op.type, "increment") + self.assertEqual(len(opts), 4) + self.assertEqual( + [op.type for op in opts], + ["fill_constant", "elementwise_mul", "sgd", "increment"]) # Check init_program init_ops = init_program.global_block().ops @@ -121,9 +120,10 @@ class TestMomentumOptimizer(unittest.TestCase): self.assertEqual(len(momentum_optimizer.get_accumulators()), 0) opts = momentum_optimizer.create_optimization_pass( params_grads, mul_out, init_program) - self.assertEqual(len(opts), 1) - sgd_op = opts[0] - self.assertEqual(sgd_op.type, "momentum") + self.assertEqual(len(opts), 3) + sgd_op = opts[-1] + self.assertEqual([op.type for op in opts], + ["fill_constant", "elementwise_mul", "momentum"]) self.assertFalse(sgd_op.attr('use_nesterov')) # Check accumulators @@ -170,9 +170,10 @@ class TestMomentumOptimizer(unittest.TestCase): self.assertEqual(len(momentum_optimizer.get_accumulators()), 0) opts = momentum_optimizer.create_optimization_pass( params_grads, mul_out, init_program) - self.assertEqual(len(opts), 1) - sgd_op = opts[0] - self.assertEqual(sgd_op.type, "momentum") + self.assertEqual(len(opts), 3) + sgd_op = opts[-1] + self.assertEqual([op.type for op in opts], + ["fill_constant", "elementwise_mul", "momentum"]) self.assertTrue(sgd_op.attr('use_nesterov')) # Check accumulators @@ -228,9 +229,9 @@ class TestAdagradOptimizer(unittest.TestCase): self.assertEqual(len(adagrad_optimizer.get_accumulators()), 0) opts = adagrad_optimizer.create_optimization_pass(params_grads, mul_out, init_program) - self.assertEqual(len(opts), 1) - adagrad_op = opts[0] - self.assertEqual(adagrad_op.type, "adagrad") + self.assertEqual(len(opts), 3) + self.assertEqual([op.type for op in opts], + ["fill_constant", "elementwise_mul", "adagrad"]) # Check accumulators accumulators = adagrad_optimizer.get_accumulators() @@ -288,9 +289,10 @@ class TestAdamOptimizer(unittest.TestCase): self.assertEqual(len(adam_optimizer.get_accumulators()), 0) opts = adam_optimizer.create_optimization_pass(params_grads, mul_out, init_program) - self.assertEqual(len(opts), 3) - adam_op = opts[0] - self.assertEqual(adam_op.type, "adam") + self.assertEqual(len(opts), 5) + self.assertEqual( + [op.type for op in opts], + ["fill_constant", "elementwise_mul", "adam", "scale", "scale"]) # Check accumulators accumulators = adam_optimizer.get_accumulators() @@ -350,9 +352,10 @@ class TestAdamaxOptimizer(unittest.TestCase): self.assertEqual(len(adamax_optimizer.get_accumulators()), 0) opts = adamax_optimizer.create_optimization_pass(params_grads, mul_out, init_program) - self.assertEqual(len(opts), 2) - adam_op = opts[0] - self.assertEqual(adam_op.type, "adamax") + self.assertEqual(len(opts), 4) + self.assertEqual( + [op.type for op in opts], + ["fill_constant", "elementwise_mul", "adamax", "scale"]) # Check accumulators accumulators = adamax_optimizer.get_accumulators() @@ -409,9 +412,10 @@ class TestDecayedAdagradOptimizer(unittest.TestCase): self.assertEqual(len(decayed_adagrad_optimizer.get_accumulators()), 0) opts = decayed_adagrad_optimizer.create_optimization_pass( params_grads, mul_out, init_program) - self.assertEqual(len(opts), 1) - decayed_adagrad_op = opts[0] - self.assertEqual(decayed_adagrad_op.type, "decayed_adagrad") + self.assertEqual(len(opts), 3) + self.assertEqual( + [op.type for op in opts], + ["fill_constant", "elementwise_mul", "decayed_adagrad"]) # Check accumulators accumulators = decayed_adagrad_optimizer.get_accumulators()