提交 c3b009a0 编写于 作者: P peizhilin

Merge branch 'windows/build' into windows/online

test=develop
...@@ -347,72 +347,70 @@ def _copy_reader_create_op_(block, op): ...@@ -347,72 +347,70 @@ def _copy_reader_create_op_(block, op):
return new_op return new_op
if os.name != 'nt': @templatedoc(op_type='create_recordio_file_reader')
def open_recordio_file(filename,
@templatedoc(op_type='create_recordio_file_reader') shapes,
def open_recordio_file(filename, lod_levels,
shapes, dtypes,
lod_levels, pass_num=1,
dtypes, for_parallel=True):
pass_num=1, """
for_parallel=True): ${comment}
"""
${comment}
Args:
filename(${filename_type}): ${filename_comment}.
shapes(list): List of tuples which declaring data shapes.
lod_levels(${lod_levels_type}): ${lod_levels_comment}.
dtypes(list): List of strs which declaring data type.
pass_num(int): Number of passes to run.
for_parallel(Bool): Set it as True if you are going to run
subsequent operators in parallel.
Returns:
${out_comment}.
Examples:
>>> import paddle.fluid as fluid
>>> reader = fluid.layers.io.open_recordio_file(
>>> filename='./data.recordio',
>>> shapes=[(3,224,224), (1)],
>>> lod_levels=[0, 0],
>>> dtypes=['float32', 'int64'])
>>> # Via the reader, we can use 'read_file' layer to get data:
>>> image, label = fluid.layers.io.read_file(reader)
"""
dtypes = [convert_np_dtype_to_dtype_(dt) for dt in dtypes]
shape_concat = []
ranks = []
for shape in shapes: Args:
shape_concat.extend(shape) filename(${filename_type}): ${filename_comment}.
ranks.append(len(shape)) shapes(list): List of tuples which declaring data shapes.
lod_levels(${lod_levels_type}): ${lod_levels_comment}.
dtypes(list): List of strs which declaring data type.
pass_num(int): Number of passes to run.
for_parallel(Bool): Set it as True if you are going to run
subsequent operators in parallel.
var_name = unique_name('open_recordio_file') Returns:
${out_comment}.
startup_blk = default_startup_program().current_block() Examples:
startup_var = startup_blk.create_var(name=var_name)
startup_blk.append_op(
type='create_recordio_file_reader',
outputs={'Out': [startup_var]},
attrs={
'shape_concat': shape_concat,
'lod_levels': lod_levels,
'filename': filename,
'ranks': ranks
})
startup_var.desc.set_dtypes(dtypes) >>> import paddle.fluid as fluid
startup_var.persistable = True >>> reader = fluid.layers.io.open_recordio_file(
main_prog_var = _copy_reader_var_( >>> filename='./data.recordio',
default_main_program().current_block(), startup_var) >>> shapes=[(3,224,224), (1)],
>>> lod_levels=[0, 0],
>>> dtypes=['float32', 'int64'])
>>> # Via the reader, we can use 'read_file' layer to get data:
>>> image, label = fluid.layers.io.read_file(reader)
"""
dtypes = [convert_np_dtype_to_dtype_(dt) for dt in dtypes]
shape_concat = []
ranks = []
for shape in shapes:
shape_concat.extend(shape)
ranks.append(len(shape))
if pass_num > 1: var_name = unique_name('open_recordio_file')
main_prog_var = multi_pass(reader=main_prog_var, pass_num=pass_num)
return monkey_patch_reader_methods(main_prog_var) startup_blk = default_startup_program().current_block()
startup_var = startup_blk.create_var(name=var_name)
startup_blk.append_op(
type='create_recordio_file_reader',
outputs={'Out': [startup_var]},
attrs={
'shape_concat': shape_concat,
'lod_levels': lod_levels,
'filename': filename,
'ranks': ranks
})
startup_var.desc.set_dtypes(dtypes)
startup_var.persistable = True
main_prog_var = _copy_reader_var_(
default_main_program().current_block(), startup_var)
if pass_num > 1:
main_prog_var = multi_pass(reader=main_prog_var, pass_num=pass_num)
return monkey_patch_reader_methods(main_prog_var)
def random_data_generator(low, high, shapes, lod_levels, for_parallel=True): def random_data_generator(low, high, shapes, lod_levels, for_parallel=True):
......
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