提交 d9edd6ef 编写于 作者: F fengjiayi

refine error msg and add unittest for cpp reader

上级 b1869f16
......@@ -47,27 +47,13 @@ def as_numpy(tensor):
return [as_numpy(t) for t in tensor]
assert isinstance(tensor, core.LoDTensor)
lod = tensor.lod()
tensor_data = np.array(tensor)
if len(lod) == 0:
ans = tensor_data
else:
raise RuntimeError("LoD Calculate lacks unit tests and buggy")
# elif len(lod) == 1:
# ans = []
# idx = 0
# while idx < len(lod) - 1:
# ans.append(tensor_data[lod[idx]:lod[idx + 1]])
# idx += 1
# else:
# for l in reversed(lod):
# ans = []
# idx = 0
# while idx < len(l) - 1:
# ans.append(tensor_data[l[idx]:l[idx + 1]])
# idx += 1
# tensor_data = ans
# ans = tensor_data
return ans
if len(lod) > 0:
raise RuntimeError(
"Some of your featched tensors hold LoD information. \
They can not be completely cast to Python ndarray. \
Please set the parameter 'return_numpy' as 'False' to \
return LoDTensor itself directly.")
return np.array(tensor)
def has_feed_operators(block, feed_targets, feed_holder_name):
......@@ -306,7 +292,6 @@ class Executor(object):
core.get_fetch_variable(scope, fetch_var_name, i)
for i in xrange(len(fetch_list))
]
if return_numpy:
outs = as_numpy(outs)
return outs
......@@ -32,31 +32,43 @@ create_random_data_generator_op = block.append_op(
"min": 0.0,
"max": 1.0
})
shuffle_reader = block.create_var(
type=fluid.core.VarDesc.VarType.READER, name="ShuffleReader")
shuffle_reader.desc.set_lod_levels([0, 0])
out1 = block.create_var(
type=fluid.core.VarDesc.VarType.LOD_TENSOR,
name="Out1",
shape=[10, 2],
dtype="float32",
lod_level=1)
out2 = block.create_var(
type=fluid.core.VarDesc.VarType.LOD_TENSOR,
name="Out2",
shape=[10, 1],
dtype="float32",
lod_level=1)
create_shuffle_reader_op = block.append_op(
type="create_shuffle_reader",
inputs={"UnderlyingReader": random_reader},
outputs={"Out": shuffle_reader},
attrs={"buffer_size": 7})
batch_reader = block.create_var(
type=fluid.core.VarDesc.VarType.READER, name="BatchReader")
batch_reader.desc.set_lod_levels([1, 1])
create_batch_reader_op = block.append_op(
type="create_batch_reader",
inputs={"UnderlyingReader": shuffle_reader},
outputs={"Out": batch_reader},
attrs={"batch_size": 10})
out1 = block.create_var(type=fluid.core.VarDesc.VarType.LOD_TENSOR, name="Out1")
out2 = block.create_var(type=fluid.core.VarDesc.VarType.LOD_TENSOR, name="Out2")
read_op = block.append_op(
type="read",
inputs={"Reader": random_reader},
type="read", inputs={"Reader": batch_reader},
outputs={"Out": [out1, out2]})
place = fluid.CPUPlace()
exe = fluid.Executor(place)
[res1, res2] = exe.run(prog, fetch_list=[out1, out2])
[res1, res2] = exe.run(prog, fetch_list=[out1, out2], return_numpy=False)
test_pass = res1.lod() == [range(0, 11)] and res1.lod() == [
range(0, 11)
] and np.array(res1).shape == (10, 2) and np.array(res2).shape == (10, 1)
if len(res1) == 0 or len(res2) == 0:
if not test_pass:
exit(1)
exit(0)
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