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提交 47853608 authored 作者: Iban Harlouchet's avatar Iban Harlouchet
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flake8 for tensor/type.py ; one E left

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theano/tensor/type.py
浏览文件 @ 47853608
import logging
_logger = logging.getLogger("theano.tensor.type")
import warnings
import numpy
import theano
from theano import config
from theano.gof import Constant, hashtype, Type, Variable
from theano.gof.utils import MethodNotDefined
from theano.gof import hashtype, Type, Variable
from theano import scalar as scal
_logger = logging.getLogger("theano.tensor.type")
class TensorType(Type):
"""Symbolic `Type` representing a numpy.ndarray value."""
......@@ -39,7 +40,7 @@ class TensorType(Type):
if self.dtype == 'floatX':
self.dtype = config.floatX
# broadcastable is immutable, and all elements are either
### True or False
# True or False
self.broadcastable = tuple(bool(b) for b in broadcastable)
self.dtype_specs() # error checking is done there
self.name = name
......@@ -74,17 +75,17 @@ class TensorType(Type):
# input (typical mistake, especially with shared variables).
if isinstance(data, Variable):
raise TypeError(
'Expected an array-like object, but found a Variable: '
'maybe you are trying to call a function on a (possibly '
'shared) variable instead of a numeric array?')
'Expected an array-like object, but found a Variable: '
'maybe you are trying to call a function on a (possibly '
'shared) variable instead of a numeric array?')
if ((type(data) is numpy.ndarray)
and (data.dtype == self.numpy_dtype)):
if ((type(data) is numpy.ndarray) and
(data.dtype == self.numpy_dtype)):
if data.dtype.num != self.numpy_dtype.num:
data = theano._asarray(data, dtype=self.dtype)
# -- now fall through to ndim check
elif((type(data) is numpy.memmap)
and (data.dtype == self.numpy_dtype)):
elif ((type(data) is numpy.memmap) and
(data.dtype == self.numpy_dtype)):
# numpy.memmap is a "safe" subclass of ndarray,
# so we can use it whereever we expect a base ndarray.
# however, casting it would defeat the purpose of not
......@@ -95,11 +96,11 @@ class TensorType(Type):
# we raise a meaningful TypeError.
if not (type(data) is numpy.ndarray):
raise TypeError("%s expected a ndarray object." % self,
data, type(data))
data, type(data))
if data.dtype != self.numpy_dtype:
raise TypeError(("%s expected a ndarray object with "
"dtype = %s (got %s).") % (
self, self.numpy_dtype, data.dtype))
"dtype = %s (got %s).") %
(self, self.numpy_dtype, data.dtype))
assert False, "This point should never be reached."
else:
if allow_downcast:
......@@ -185,7 +186,7 @@ class TensorType(Type):
" dimension.", data.shape, self.broadcastable)
i += 1
if (self.filter_checks_isfinite and
not numpy.all(numpy.isfinite(data))):
not numpy.all(numpy.isfinite(data))):
raise ValueError("non-finite elements not allowed")
return data
......@@ -208,14 +209,12 @@ class TensorType(Type):
return other
raise TypeError(
'Cannot convert Type %(othertype)s '
'(of Variable %(other)s) into Type %(self)s. '
'You can try to manually convert %(other)s into a %(self)s.'
% dict(
othertype=other.type,
other=other,
self=self)
)
'Cannot convert Type %(othertype)s '
'(of Variable %(other)s) into Type %(self)s. '
'You can try to manually convert %(other)s into a %(self)s.' %
dict(othertype=other.type,
other=other,
self=self))
def value_validity_msg(self, a):
try:
......@@ -247,10 +246,10 @@ class TensorType(Type):
'int64': (int, 'npy_int64', 'NPY_INT64'),
'complex128': (complex, 'theano_complex128', 'NPY_COMPLEX128'),
'complex64': (complex, 'theano_complex64', 'NPY_COMPLEX64')
}[self.dtype]
}[self.dtype]
except KeyError:
raise TypeError("Unsupported dtype for %s: %s"
% (self.__class__.__name__, self.dtype))
% (self.__class__.__name__, self.dtype))
def to_scalar_type(self):
return scal.get_scalar_type(dtype=self.dtype)
......@@ -265,7 +264,7 @@ class TensorType(Type):
self.dtype == var.type.dtype and
self.ndim == var.type.ndim and
all(sb == ob or ob for sb, ob in zip(self.broadcastable,
var.type.broadcastable))):
var.type.broadcastable))):
return theano.tensor.patternbroadcast(var, self.broadcastable)
@staticmethod
......@@ -351,7 +350,7 @@ class TensorType(Type):
rtol = 1.0000000000000001e-05
atol = 1e-8
cmp_elemwise = (numpy.absolute(a - b) <=
(atol + rtol * numpy.absolute(b)))
(atol + rtol * numpy.absolute(b)))
# Find places where both a and b have missing values.
both_missing = a_missing * numpy.isnan(b)
......@@ -361,9 +360,9 @@ class TensorType(Type):
# cmp_elemwise is weird when we have inf and -inf.
# set it to False
cmp_elemwise = numpy.where(
both_inf & cmp_elemwise,
a == b,
cmp_elemwise)
both_inf & cmp_elemwise,
a == b,
cmp_elemwise)
# check the sign of the inf
both_inf = numpy.where(both_inf, (a == b), both_inf)
......@@ -383,7 +382,7 @@ class TensorType(Type):
return hashtype(self) ^ hash(self.dtype) ^ hash(self.broadcastable)
ndim = property(lambda self: len(self.broadcastable),
doc="number of dimensions")
doc="number of dimensions")
"""Number of dimensions
This read-only property is the preferred way to get the number of
......@@ -407,10 +406,10 @@ class TensorType(Type):
else:
b = self.broadcastable
named_broadcastable = {(): 'scalar',
(False,): 'vector',
(False, True): 'col',
(True, False): 'row',
(False, False): 'matrix'}
(False,): 'vector',
(False, True): 'col',
(True, False): 'row',
(False, False): 'matrix'}
if b in named_broadcastable:
bcast = named_broadcastable[b]
else:
......@@ -422,7 +421,7 @@ class TensorType(Type):
def __repr__(self):
return str(self)
#"TensorType{%s, %s}" % (str(self.dtype), str(self.broadcastable))
# "TensorType{%s, %s}" % (str(self.dtype), str(self.broadcastable))
def c_declare(self, name, sub, check_input=True):
"""Override `CLinkerType.c_declare` """
......@@ -636,13 +635,13 @@ def values_eq_approx_always_true(a, b):
# Register TensorType C code for ViewOp.
theano.compile.register_view_op_c_code(
TensorType,
"""
Py_XDECREF(%(oname)s);
%(oname)s = %(iname)s;
Py_XINCREF(%(oname)s);
""",
version=1)
TensorType,
"""
Py_XDECREF(%(oname)s);
%(oname)s = %(iname)s;
Py_XINCREF(%(oname)s);
""",
version=1)
# Register TensorType C code for Shape Op.
......@@ -665,51 +664,51 @@ theano.compile.register_shape_c_code(
# Register TensorType C code for ViewOp.
theano.compile.register_shape_i_c_code(
TensorType,
"""
if(!%(oname)s)
%(oname)s=(PyArrayObject*)PyArray_EMPTY(0, NULL, NPY_INT64, 0);
((npy_int64*)PyArray_DATA(%(oname)s))[0]=PyArray_DIMS(%(iname)s)[%(i)s];
""",
"""
if (%(i)s>=PyArray_NDIM(%(iname)s)){
PyErr_SetString(PyExc_TypeError,
"Number of dimensions lower than expected");
%(fail)s
}
""",
version=3)
TensorType,
"""
if(!%(oname)s)
%(oname)s=(PyArrayObject*)PyArray_EMPTY(0, NULL, NPY_INT64, 0);
((npy_int64*)PyArray_DATA(%(oname)s))[0]=PyArray_DIMS(%(iname)s)[%(i)s];
""",
"""
if (%(i)s>=PyArray_NDIM(%(iname)s)){
PyErr_SetString(PyExc_TypeError,
"Number of dimensions lower than expected");
%(fail)s
}
""",
version=3)
# Register TensorType C code for DeepCopyOp
theano.compile.register_deep_copy_op_c_code(
TensorType,
"""
int alloc = %(oname)s == NULL;
for(int i=0; !alloc && i<PyArray_NDIM(%(oname)s); i++) {
if(PyArray_DIMS(%(iname)s)[i] != PyArray_DIMS(%(oname)s)[i]) {
alloc = true;
break;
}
TensorType,
"""
int alloc = %(oname)s == NULL;
for(int i=0; !alloc && i<PyArray_NDIM(%(oname)s); i++) {
if(PyArray_DIMS(%(iname)s)[i] != PyArray_DIMS(%(oname)s)[i]) {
alloc = true;
break;
}
}
if(alloc) {
Py_XDECREF(%(oname)s);
%(oname)s = (PyArrayObject*)PyArray_NewCopy(%(iname)s,
NPY_ANYORDER);
if (!%(oname)s)
{
PyErr_SetString(PyExc_ValueError,
"DeepCopyOp: the copy failed!");
%(fail)s;
}
if(alloc) {
Py_XDECREF(%(oname)s);
%(oname)s = (PyArrayObject*)PyArray_NewCopy(%(iname)s,
NPY_ANYORDER);
if (!%(oname)s)
{
PyErr_SetString(PyExc_ValueError,
"DeepCopyOp: the copy failed!");
%(fail)s;
}
} else {
if(PyArray_CopyInto(%(oname)s, %(iname)s)){
PyErr_SetString(PyExc_ValueError,
"DeepCopyOp: the copy failed into already allocated space!");
%(fail)s;
}
} else {
if(PyArray_CopyInto(%(oname)s, %(iname)s)){
PyErr_SetString(PyExc_ValueError,
"DeepCopyOp: the copy failed into already allocated space!");
%(fail)s;
}
""",
version=2)
}
""",
version=2)
theano.compile.register_rebroadcast_c_code(
......@@ -723,7 +722,7 @@ theano.compile.register_rebroadcast_c_code(
%(fail)s
}
""",
version=1)
version=1)
theano.compile.register_specify_shape_c_code(
......
theano/tests/test_flake8.py
浏览文件 @ 47853608
......@@ -57,7 +57,6 @@ whitelist_flake8 = [
"typed_list/tests/test_type.py",
"typed_list/tests/test_opt.py",
"typed_list/tests/test_basic.py",
"tensor/type.py",
"tensor/fourier.py",
"tensor/__init__.py",
"tensor/opt_uncanonicalize.py",
......
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