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111fa975
编写于
1月 06, 2022
作者:
M
Megvii Engine Team
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差异文件
Merge pull request #422 from Asthestarsfalll:zeroslike
GitOrigin-RevId: 4b464446b55e2619b7cc43bb321aeae8a3cb41ef
上级
48e09738
520db818
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1
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1 changed file
with
16 addition
and
29 deletion
+16
-29
imperative/python/megengine/functional/tensor.py
imperative/python/megengine/functional/tensor.py
+16
-29
未找到文件。
imperative/python/megengine/functional/tensor.py
浏览文件 @
111fa975
...
...
@@ -113,7 +113,7 @@ def full(
data type must be inferred from ``value``. If the value is an ``int``,
the output tensor data type must be the default integer data type. If the
value is a ``float``, the output tensor data type must be the default
floating-point data type. If the value is a ``bool``, the output tensor
floating-point data type. If the value is a ``bool``, the output tensor
must have boolean data type. Default: ``None``.
device: device on which to place the created tensor. Default: ``None``.
...
...
@@ -222,33 +222,20 @@ def zeros(
def
zeros_like
(
inp
:
Union
[
Tensor
,
SymbolVar
])
->
Union
[
Tensor
,
SymbolVar
]:
r
"""Returns a
zero tensor with the same sha
pe as input tensor.
r
"""Returns a
tensor filled with zeros with the same shape and data ty
pe as input tensor.
Args:
inp: input tensor.
inp
(Tensor)
: input tensor.
Return:
output tensor
.
a tensor containing zeros
.
Examples:
.. testcode::
import numpy as np
from megengine import tensor
import megengine.functional as F
inp = tensor(np.arange(1, 7, dtype=np.int32).reshape(2,3))
out = F.zeros_like(inp)
print(out.numpy())
Outputs:
.. testoutput::
[[0 0 0]
[0 0 0]]
>>> input = F.arange(9, dtype='int32').reshape(3,3)
>>> F.zeros_like(input)
Tensor([[0 0 0]
[0 0 0]
[0 0 0]], dtype=int32, device=xpux:0)
"""
return
full_like
(
inp
,
0.0
)
...
...
@@ -1095,18 +1082,18 @@ def arange(
dtype
=
"float32"
,
device
:
Optional
[
CompNode
]
=
None
,
)
->
Tensor
:
r
"""Returns evenly spaced values within the half-open interval ``[start, stop)`` as a one-dimensional tensor.
r
"""Returns evenly spaced values within the half-open interval ``[start, stop)`` as a one-dimensional tensor.
Note:
This function cannot guarantee that the interval does not include the stop value in those cases
This function cannot guarantee that the interval does not include the stop value in those cases
where step is not an integer and floating-point rounding errors affect the length of the output tensor.
Args:
start: if ``stop`` is specified, the start of interval (inclusive); otherwise,
the end of the interval (exclusive). If ``stop`` is not specified, the default starting value is ``0``.
start: if ``stop`` is specified, the start of interval (inclusive); otherwise,
the end of the interval (exclusive). If ``stop`` is not specified, the default starting value is ``0``.
stop: the end of the interval. Default: ``None``.
step: the distance between two adjacent elements ( ``out[i+1] - out[i]`` ). Must not be 0 ;
may be negative, this results i an empty tensor if stop >= start . Default: 1 .
step: the distance between two adjacent elements ( ``out[i+1] - out[i]`` ). Must not be 0 ;
may be negative, this results i an empty tensor if stop >= start . Default: 1 .
Keyword args:
dtype( :attr:`.Tensor.dtype` ): output tensor data type. Default: ``float32``.
...
...
@@ -1115,7 +1102,7 @@ def arange(
Returns:
A one-dimensional tensor containing evenly spaced values.
The length of the output tensor must be ``ceil((stop-start)/step)``
The length of the output tensor must be ``ceil((stop-start)/step)``
if ``stop - start`` and ``step`` have the same sign, and length 0 otherwise.
Examples:
...
...
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