提交 43d69818 编写于 作者: C Cao Ying 提交者: GitHub

Merge pull request #4968 from luotao1/sparse_vector

rename sparse_vector to sparse_float_vector, and fix typo.
...@@ -174,7 +174,7 @@ decoder_inputs = paddle.layer.fc( ...@@ -174,7 +174,7 @@ decoder_inputs = paddle.layer.fc(
1. 两者都是对梯度的截断,但截断时机不同,前者在 :code:`optimzier` 更新网络参数时应用;后者在激活函数反向计算时被调用; 1. 两者都是对梯度的截断,但截断时机不同,前者在 :code:`optimzier` 更新网络参数时应用;后者在激活函数反向计算时被调用;
2. 截断对象不同:前者截断可学习参数的梯度,后者截断回传给前层的梯度; 2. 截断对象不同:前者截断可学习参数的梯度,后者截断回传给前层的梯度;
除此之外,还可以通过减小学习或者对数据进行归一化处理来解决这类问题。 除此之外,还可以通过减小学习或者对数据进行归一化处理来解决这类问题。
5. 如何调用 infer 接口输出多个layer的预测结果 5. 如何调用 infer 接口输出多个layer的预测结果
----------------------------------------------- -----------------------------------------------
......
...@@ -51,7 +51,10 @@ def test_sparse_non_value_no_seq(setting, filename): ...@@ -51,7 +51,10 @@ def test_sparse_non_value_no_seq(setting, filename):
yield [(i + 1) * (j + 1) for j in xrange(10)] yield [(i + 1) * (j + 1) for j in xrange(10)]
@provider(input_types=[sparse_vector(30000, seq_type=SequenceType.NO_SEQUENCE)]) @provider(input_types=[
sparse_float_vector(
30000, seq_type=SequenceType.NO_SEQUENCE)
])
def test_sparse_value_no_seq(setting, filename): def test_sparse_value_no_seq(setting, filename):
for i in xrange(200): for i in xrange(200):
yield [((i + 1) * (j + 1), float(j) / float(i + 1)) for j in xrange(10)] yield [((i + 1) * (j + 1), float(j) / float(i + 1)) for j in xrange(10)]
......
...@@ -175,7 +175,7 @@ def index_slot(value_range, seq_type=SequenceType.NO_SEQUENCE): ...@@ -175,7 +175,7 @@ def index_slot(value_range, seq_type=SequenceType.NO_SEQUENCE):
dense_vector = dense_slot dense_vector = dense_slot
sparse_binary_vector = sparse_non_value_slot sparse_binary_vector = sparse_non_value_slot
sparse_vector = sparse_value_slot sparse_float_vector = sparse_value_slot
integer_value = index_slot integer_value = index_slot
# dense_array can be used for variable-length input feature. # dense_array can be used for variable-length input feature.
...@@ -216,7 +216,7 @@ def sparse_binary_vector_sub_sequence(dim): ...@@ -216,7 +216,7 @@ def sparse_binary_vector_sub_sequence(dim):
return sparse_binary_vector(dim, seq_type=SequenceType.SUB_SEQUENCE) return sparse_binary_vector(dim, seq_type=SequenceType.SUB_SEQUENCE)
def sparse_vector_sequence(dim): def sparse_float_vector_sequence(dim):
""" """
Data type of a sequence of sparse vector, which most elements are zero, Data type of a sequence of sparse vector, which most elements are zero,
others could be any float value. others could be any float value.
...@@ -226,11 +226,11 @@ def sparse_vector_sequence(dim): ...@@ -226,11 +226,11 @@ def sparse_vector_sequence(dim):
:return: An input type object :return: An input type object
:rtype: InputType :rtype: InputType
""" """
return sparse_vector(dim, seq_type=SequenceType.SEQUENCE) return sparse_float_vector(dim, seq_type=SequenceType.SEQUENCE)
def sparse_vector_sub_sequence(dim): def sparse_float_vector_sub_sequence(dim):
return sparse_vector(dim, seq_type=SequenceType.SUB_SEQUENCE) return sparse_float_vector(dim, seq_type=SequenceType.SUB_SEQUENCE)
def integer_value_sequence(value_range): def integer_value_sequence(value_range):
......
...@@ -97,7 +97,7 @@ class DataFeederTest(unittest.TestCase): ...@@ -97,7 +97,7 @@ class DataFeederTest(unittest.TestCase):
each_sample.append(zip(a, b)) each_sample.append(zip(a, b))
data.append(each_sample) data.append(each_sample)
feeder = DataFeeder([('input', data_type.sparse_vector(dim))], feeder = DataFeeder([('input', data_type.sparse_float_vector(dim))],
{'input': 0}) {'input': 0})
arg = feeder(data) arg = feeder(data)
output = arg.getSlotValue(0) output = arg.getSlotValue(0)
......
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