diff --git a/python/paddle/v2/framework/framework.py b/python/paddle/v2/framework/framework.py index a68f2afcfa86fcfea57fc2d07f4e7951773d3bac..eb6867a194206c908b2a4a265a1cd983d33d6b56 100644 --- a/python/paddle/v2/framework/framework.py +++ b/python/paddle/v2/framework/framework.py @@ -15,7 +15,7 @@ class Variable(object): shape=None, dtype=None, lod_level=None, - persistable=False, + persistable=None, **kwargs): self.block = block diff --git a/python/paddle/v2/framework/layer_helper.py b/python/paddle/v2/framework/layer_helper.py index 6615bdcd3b1afa493c9ad05c789664818e64d2f2..ae7255ef9acff6975012626c387adc4d13fb722e 100644 --- a/python/paddle/v2/framework/layer_helper.py +++ b/python/paddle/v2/framework/layer_helper.py @@ -121,10 +121,13 @@ class LayerHelper(object): def create_tmp_variable(self, dtype): return self.program.current_block().create_var( - name=unique_name(".".join([self.name, 'tmp'])), dtype=dtype) + name=unique_name(".".join([self.name, 'tmp'])), + dtype=dtype, + persistable=False) def create_global_variable(self, *args, **kwargs): - return self.program.global_block().create_var(*args, **kwargs) + return self.program.global_block().create_var( + *args, persistable=False, **kwargs) def append_bias_op(self, input_var): size = list(input_var.shape[1:]) diff --git a/python/paddle/v2/framework/tests/image/ranges.png b/python/paddle/v2/framework/tests/image/ranges.png new file mode 100644 index 0000000000000000000000000000000000000000..f1341341c98ea74af450fc75014e4b26c5550687 Binary files /dev/null and b/python/paddle/v2/framework/tests/image/ranges.png differ diff --git a/python/paddle/v2/framework/tests/test_fit_a_line.py b/python/paddle/v2/framework/tests/test_fit_a_line.py index 35aee59bb2750b5b305c593d54a58bbd0b4d92d2..a686ad2010a95a4fb81e6b36c2e99cd134404ef2 100644 --- a/python/paddle/v2/framework/tests/test_fit_a_line.py +++ b/python/paddle/v2/framework/tests/test_fit_a_line.py @@ -20,9 +20,12 @@ avg_cost = layers.mean(x=cost, program=program) sgd_optimizer = optimizer.SGDOptimizer(learning_rate=0.01) opts = sgd_optimizer.minimize(avg_cost) -# print str(program) +print str(program) -BATCH_SIZE = 2 +import pdb +pdb.set_trace() + +BATCH_SIZE = 100 train_reader = paddle.batch( paddle.reader.shuffle( @@ -32,12 +35,12 @@ train_reader = paddle.batch( place = core.CPUPlace() exe = Executor(place) -PASS_NUM = 1 +PASS_NUM = 200 for pass_id in range(PASS_NUM): for data in train_reader(): x_data = np.array(map(lambda x: x[0], data)).astype("float32") y_data = np.array(map(lambda x: x[1], data)).astype("float32") - y_data = np.expand_dims(y_data, axis=1) + #y_data = np.expand_dims(y_data, axis=1) tensor_x = core.LoDTensor() tensor_x.set(x_data, place)