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提交 11faef91 authored 作者: Olivier Breuleux's avatar Olivier Breuleux
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splitted inplace ops from tensor.basic

上级 501dc901
隐藏空白字符变更
内嵌 并排
正在显示 包含 205 行增加 和 174 行删除
scripts/test.py
浏览文件 @ 11faef91
......@@ -4,7 +4,7 @@ theano_path = os.path.realpath("%s/.." % sys.path[0])
sys.path[0:0] = [theano_path]
def test_module(module_path, debugmode = False):
files = commands.getoutput("find %s -name _test_*.py" % module_path)
files = commands.getoutput("find %s -name test_*.py" % module_path)
suite = None
tocut = len("/".join(module_path.split("/")[:-1])) + 1
for file in files.split("\n"):
......
theano/scalar/__init__.py
浏览文件 @ 11faef91
from basic import *
from basic import _abs
theano/scalar/basic.py
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......@@ -183,7 +183,7 @@ complex_types = complex64, complex128
class _scalar_py_operators:
#UNARY
def __abs__(self): return _abs(self)
def __abs__(self): return abs_(self)
def __neg__(self): return neg(self)
#CASTS
......@@ -587,7 +587,7 @@ class Abs(UnaryScalarOp):
return "%(z)s = fabs(%(x)s);" % locals()
#complex, other?
raise NotImplementedError('type not supported', type)
_abs = Abs(same_out)
abs_ = Abs(same_out)
class Sgn(UnaryScalarOp):
def impl(self, x):
......
theano/scalar/tests/_test_basic.py → theano/scalar/tests/test_basic.py
浏览文件 @ 11faef91
......@@ -11,7 +11,7 @@ def inputs():
return floats('xyz')
class _test_ScalarOps(unittest.TestCase):
class test_ScalarOps(unittest.TestCase):
def test_straightforward(self):
x, y, z = inputs()
......@@ -21,7 +21,7 @@ class _test_ScalarOps(unittest.TestCase):
assert fn(1.0, 2.0) == 1.5
class _test_composite(unittest.TestCase):
class test_composite(unittest.TestCase):
def test_straightforward(self):
x, y, z = inputs()
......@@ -57,7 +57,7 @@ class _test_composite(unittest.TestCase):
assert fn(1.0, 2.0, 3.0) == [6.0, 7.0, 0.5]
class _test_logical(unittest.TestCase):
class test_logical(unittest.TestCase):
def test_gt(self):
x, y, z = inputs()
fn = gof.DualLinker().accept(Env([x,y], [x > y])).make_function()
......
theano/sparse/tests/_test_basic.py → theano/sparse/tests/test_basic.py
浏览文件 @ 11faef91
......@@ -147,7 +147,7 @@ class T_conversion(unittest.TestCase):
self.failUnless(numpy.all(val[0] == [1,0,0,0,0]))
class _testCase_dot(unittest.TestCase):
class test_dot(unittest.TestCase):
def setUp(self):
numpy.random.seed(44)
......
theano/tensor/basic.py
浏览文件 @ 11faef91
......@@ -450,7 +450,7 @@ cols, fcols, dcols, icols, lcols = _multi(col, fcol, dcol, icol, lcol)
class _tensor_py_operators:
#UNARY
def __abs__(self): return _abs(self)
def __abs__(self): return abs_(self)
def __neg__(self): return neg(self)
#CASTS
......@@ -472,9 +472,9 @@ class _tensor_py_operators:
def __rand__(self,other): return and_(other,self)
def __ror__(self,other): return or_(other, self)
def __rxor__(self,other): return xor(other, self)
def __iand__(self, other): return _and_inplace(self, other)
def __ior__(self, other): return _or_inplace(self, other)
def __ixor__(self, other): return _xor_inplace(self, other)
# def __iand__(self, other): return _and_inplace(self, other)
# def __ior__(self, other): return _or_inplace(self, other)
# def __ixor__(self, other): return _xor_inplace(self, other)
#ARITHMETIC - NORMAL
def __add__(self,other): return add(self,other)
......@@ -484,12 +484,12 @@ class _tensor_py_operators:
def __pow__(self,other): return pow(self,other)
def __mod__(self,other): return mod(self,other)
#ARITHMETIC - INPLACE
def __iadd__(self,other): return _add_inplace(self,other)
def __isub__(self,other): return _sub_inplace(self,other)
def __imul__(self,other): return _mul_inplace(self,other)
def __idiv__(self,other): return _div_inplace(self,other)
def __ipow__(self,other): return _pow_inplace(self,other)
# #ARITHMETIC - INPLACE
# def __iadd__(self,other): return _add_inplace(self,other)
# def __isub__(self,other): return _sub_inplace(self,other)
# def __imul__(self,other): return _mul_inplace(self,other)
# def __idiv__(self,other): return _div_inplace(self,other)
# def __ipow__(self,other): return _pow_inplace(self,other)
#ARITHMETIC - RIGHT-OPERAND
def __radd__(self,other): return add(other,self)
......@@ -562,7 +562,7 @@ elemwise.TensorValue = TensorValue
def _elemwise(scalar_op, name, doc_prefix=''):
straight = elemwise.Elemwise(scalar_op, name = name)
inplace_scalar_op = scalar_op.__class__(scal.transfer_type(0))
inplace = elemwise.Elemwise(inplace_scalar_op, {0: 0}, name = '_'+name+"_inplace")
inplace = elemwise.Elemwise(inplace_scalar_op, {0: 0}, name = name+"_inplace")
# don't add the inplace versions, they aren't supposed to be part of the user interface
_constructor_list.append(straight)
......@@ -599,7 +599,7 @@ def _scal_elemwise(symbol):
inplace = symbolname.endswith('_inplace')
if inplace:
scalar_op = getattr(scal, symbolname[1:-len('_inplace')])
scalar_op = getattr(scal, symbolname[:-len('_inplace')])
inplace_scalar_op = scalar_op.__class__(scal.transfer_type(0))
rval = elemwise.Elemwise(inplace_scalar_op, {0: 0}, name=symbolname)
else:
......@@ -780,50 +780,26 @@ def argmax(x, axis=None):
def lt(a, b):
"""a < b"""
@_scal_elemwise
def _lt_inplace(a,b):
"""a < b (inplace on a)"""
@_scal_elemwise
def gt(a, b):
"""a > b"""
@_scal_elemwise
def _gt_inplace(a,b):
"""a > b (inplace on a)"""
@_scal_elemwise
def le(a, b):
"""a <= b"""
@_scal_elemwise
def _le_inplace(a,b):
"""a <= b (inplace on a)"""
@_scal_elemwise
def ge(a, b):
"""a >= b"""
@_scal_elemwise
def _ge_inplace(a,b):
"""a >= b (inplace on a)"""
@_scal_elemwise
def eq(a, b):
"""a == b"""
@_scal_elemwise
def _eq_inplace(a,b):
"""a == b (inplace on a)"""
@_scal_elemwise
def neq(a, b):
"""a != b"""
@_scal_elemwise
def _neq_inplace(a,b):
"""a != b (inplace on a)"""
##########################
# Bit-wise
......@@ -833,148 +809,86 @@ def _neq_inplace(a,b):
def and_(a,b):
"""bitwise a & b"""
@_scal_elemwise
def _and__inplace(a,b):
"""bitwise a & b (inplace on a)"""
@_scal_elemwise
def or_(a,b):
"""bitwise a | b"""
@_scal_elemwise
def _or__inplace(a,b):
"""bitwise a | b (inplace on a)"""
@_scal_elemwise
def xor(a,b):
"""bitwise a ^ b"""
@_scal_elemwise
def _xor_inplace(a,b):
"""bitwise a ^ b (inplace on a)"""
@_scal_elemwise
def invert(a):
"""bitwise ~a"""
@_scal_elemwise
def _invert_inplace(a):
"""bitwise ~a (inplace on a)"""
##########################
# Math
##########################
@_scal_elemwise
def _abs(a):
def abs_(a):
"""|`a`|
_abs has a leading underscore because abs() is a builtin. TensorResult overloads the
`TensorResult.__abs__` operator so that this function is called when you type abs(a).
TensorResult overloads the `TensorResult.__abs__` operator so that
this function is called when you type abs(a).
"""
@_scal_elemwise
def __abs_inplace(a):
"""|`a`| (inplace on `a`)"""
@_scal_elemwise
def exp(a):
"""e^`a`"""
@_scal_elemwise
def _exp_inplace(a):
"""e^`a` (inplace on `a`)"""
@_scal_elemwise
def neg(a):
"""-a"""
@_scal_elemwise
def _neg_inplace(a):
"""-a (inplace on a)"""
@_scal_elemwise
def inv(a):
"""1.0/a (inplace on a)"""
@_scal_elemwise
def _inv_inplace(a):
"""1.0/a (inplace on a)"""
@_scal_elemwise
def log(a):
"""base e logarithm of a"""
@_scal_elemwise
def _log_inplace(a):
"""base e logarithm of a (inplace on a)"""
@_scal_elemwise
def log2(a):
"""base 2 logarithm of a"""
@_scal_elemwise
def _log2_inplace(a):
"""base 2 logarithm of a (inplace on a)"""
@_scal_elemwise
def sgn(a):
"""sign of a"""
@_scal_elemwise
def _sgn_inplace(a):
"""sign of `a` (inplace on `a`)"""
@_scal_elemwise
def sqr(a):
"""square of a"""
@_scal_elemwise
def _sqr_inplace(a):
"""square of `a` (inplace on `a`)"""
@_scal_elemwise
def sqrt(a):
"""square root of a"""
@_scal_elemwise
def _sqrt_inplace(a):
"""square root of `a` (inplace on `a`)"""
@_scal_elemwise
def cos(a):
"""cosine of a"""
@_scal_elemwise
def _cos_inplace(a):
"""cosine of `a` (inplace on `a`)"""
@_scal_elemwise
def sin(a):
"""sine of a"""
@_scal_elemwise
def _sin_inplace(a):
"""sine of `a` (inplace on `a`)"""
@_scal_elemwise
def tan(a):
"""tangent of a"""
@_scal_elemwise
def _tan_inplace(a):
"""tangent of `a` (inplace on `a`)"""
@_scal_elemwise
def cosh(a):
"""hyperbolic cosine of a"""
@_scal_elemwise
def _cosh_inplace(a):
"""hyperbolic cosine of `a` (inplace on `a`)"""
@_scal_elemwise
def sinh(a):
"""hyperbolic sine of a"""
@_scal_elemwise
def _sinh_inplace(a):
"""hyperbolic sine of `a` (inplace on `a`)"""
@_scal_elemwise
def tanh(a):
"""hyperbolic tangent of a"""
@_scal_elemwise
def _tanh_inplace(a):
"""hyperbolic tangent of `a` (inplace on `a`)"""
##########################
......@@ -986,12 +900,8 @@ def _tanh_inplace(a):
@_scal_elemwise
def second(a, b):
"""Create a matrix by filling the shape of a with b"""
@_scal_elemwise
def _second_inplace(a):
"""Fill `a` with `b`"""
fill = second
_fill_inplace = _second_inplace
@constructor
def ones_like(model):
......@@ -1112,44 +1022,26 @@ repeat = Repeat()
@_scal_elemwise
def add(a, b):
"""elementwise addition"""
@_scal_elemwise
def _add_inplace(a, b):
"""elementwise addition (inplace on `a`)"""
@_scal_elemwise
def sub(a, b):
"""elementwise subtraction"""
@_scal_elemwise
def _sub_inplace(a, b):
"""elementwise subtraction (inplace on `a`)"""
@_scal_elemwise
def mul(a, b):
"""elementwise multiplication"""
@_scal_elemwise
def _mul_inplace(a, b):
"""elementwise multiplication (inplace on `a`)"""
@_scal_elemwise
def div(a, b):
"""elementwise division"""
@_scal_elemwise
def _div_inplace(a, b):
"""elementwise division (inplace on `a`)"""
@_scal_elemwise
def mod(a, b):
"""elementwise modulo"""
@_scal_elemwise
def _mod_inplace(a, b):
"""elementwise modulo (inplace on `a`)"""
@_scal_elemwise
def pow(a, b):
"""elementwise power"""
@_scal_elemwise
def _pow_inplace(a, b):
"""elementwise power (inplace on `a`)"""
##########################
......@@ -1182,7 +1074,6 @@ class TransposeInplace(Op):
return "TransposeView"
_transpose_inplace = TransposeInplace()
"""WRITEME"""
def transpose(x, **kwargs):
"""WRITEME"""
......
theano/tensor/inplace.py 0 → 100644
浏览文件 @ 11faef91
from basic import _scal_elemwise, _transpose_inplace
@_scal_elemwise
def lt_inplace(a,b):
"""a < b (inplace on a)"""
@_scal_elemwise
def gt_inplace(a,b):
"""a > b (inplace on a)"""
@_scal_elemwise
def le_inplace(a,b):
"""a <= b (inplace on a)"""
@_scal_elemwise
def ge_inplace(a,b):
"""a >= b (inplace on a)"""
@_scal_elemwise
def eq_inplace(a,b):
"""a == b (inplace on a)"""
@_scal_elemwise
def neq_inplace(a,b):
"""a != b (inplace on a)"""
@_scal_elemwise
def and__inplace(a,b):
"""bitwise a & b (inplace on a)"""
@_scal_elemwise
def or__inplace(a,b):
"""bitwise a | b (inplace on a)"""
@_scal_elemwise
def xor_inplace(a,b):
"""bitwise a ^ b (inplace on a)"""
@_scal_elemwise
def invert_inplace(a):
"""bitwise ~a (inplace on a)"""
@_scal_elemwise
def abs__inplace(a):
"""|`a`| (inplace on `a`)"""
@_scal_elemwise
def exp_inplace(a):
"""e^`a` (inplace on `a`)"""
@_scal_elemwise
def neg_inplace(a):
"""-a (inplace on a)"""
@_scal_elemwise
def inv_inplace(a):
"""1.0/a (inplace on a)"""
@_scal_elemwise
def log_inplace(a):
"""base e logarithm of a (inplace on a)"""
@_scal_elemwise
def log2_inplace(a):
"""base 2 logarithm of a (inplace on a)"""
@_scal_elemwise
def sgn_inplace(a):
"""sign of `a` (inplace on `a`)"""
@_scal_elemwise
def sqr_inplace(a):
"""square of `a` (inplace on `a`)"""
@_scal_elemwise
def sqrt_inplace(a):
"""square root of `a` (inplace on `a`)"""
@_scal_elemwise
def cos_inplace(a):
"""cosine of `a` (inplace on `a`)"""
@_scal_elemwise
def sin_inplace(a):
"""sine of `a` (inplace on `a`)"""
@_scal_elemwise
def tan_inplace(a):
"""tangent of `a` (inplace on `a`)"""
@_scal_elemwise
def cosh_inplace(a):
"""hyperbolic cosine of `a` (inplace on `a`)"""
@_scal_elemwise
def sinh_inplace(a):
"""hyperbolic sine of `a` (inplace on `a`)"""
@_scal_elemwise
def tanh_inplace(a):
"""hyperbolic tangent of `a` (inplace on `a`)"""
@_scal_elemwise
def second_inplace(a):
"""Fill `a` with `b`"""
fill_inplace = second_inplace
@_scal_elemwise
def add_inplace(a, b):
"""elementwise addition (inplace on `a`)"""
@_scal_elemwise
def sub_inplace(a, b):
"""elementwise subtraction (inplace on `a`)"""
@_scal_elemwise
def mul_inplace(a, b):
"""elementwise multiplication (inplace on `a`)"""
@_scal_elemwise
def div_inplace(a, b):
"""elementwise division (inplace on `a`)"""
@_scal_elemwise
def mod_inplace(a, b):
"""elementwise modulo (inplace on `a`)"""
@_scal_elemwise
def pow_inplace(a, b):
"""elementwise power (inplace on `a`)"""
transpose_inplace = _transpose_inplace
"""WRITEME"""
theano/tensor/opt.py
浏览文件 @ 11faef91
......@@ -8,6 +8,7 @@ from ..gof import opt
from elemwise import Elemwise, DimShuffle
from .. import scalar
import basic as T
import inplace as I
import numpy as N
import operator
import itertools
......@@ -30,7 +31,7 @@ def in2out(*local_opts):
# gemm: (d,a,b,c,s) -> d = d*s + a*dot(b,c)
# Transforms d -= a * dot(b, c) into gemm(d, -a, b, c, 1.0)
gemm_pattern_1 = gof.PatternSub((T._sub_inplace,
gemm_pattern_1 = gof.PatternSub((I.sub_inplace,
'd',
(T.mul,
dict(pattern = (T.DimShuffle((), ['x', 'x'], inplace = True), 'a'),
......
theano/tensor/tests/test_basic.py
浏览文件 @ 11faef91
......@@ -3,6 +3,7 @@ import operator
from theano.tensor import *
from theano.tensor import basic as tensor # for hidden symbols
from theano.tensor import inplace
import unittest
from copy import copy
......@@ -232,7 +233,9 @@ AddTester = make_broadcast_restet(op = add,
**_good_broadcast_binary_normal),
bad_build = _bad_build_broadcast_binary_normal,
bad_runtime = _bad_runtime_broadcast_binary_normal)
AddInplaceTester = make_broadcast_restet(op = tensor._add_inplace,
AddInplaceTester = make_broadcast_restet(op = inplace.add_inplace,
expected = lambda x, y: x + y,
good = _good_broadcast_binary_normal,
bad_build = _bad_build_broadcast_binary_normal,
......@@ -246,7 +249,7 @@ SubTester = make_broadcast_restet(op = sub,
bad_runtime = _bad_runtime_broadcast_binary_normal,
grad = _grad_broadcast_binary_normal)
SubInplaceTester = make_broadcast_restet(op = tensor._sub_inplace,
SubInplaceTester = make_broadcast_restet(op = inplace.sub_inplace,
expected = lambda x, y: x - y,
good = _good_broadcast_binary_normal,
bad_build = _bad_build_broadcast_binary_normal,
......@@ -264,7 +267,7 @@ MulTester = make_broadcast_restet(op = mul,
grad = dict(three_inputs_same_shapes = (rand(2, 3), rand(2, 3), rand(2, 3)),
four_inputs_broadcast = (rand(2, 3), rand(1, 3), rand(2, 1), rand(1, 1)),
**_grad_broadcast_binary_normal))
MulInplaceTester = make_broadcast_restet(op = tensor._mul_inplace,
MulInplaceTester = make_broadcast_restet(op = inplace.mul_inplace,
expected = lambda x, y: x * y,
good = _good_broadcast_binary_normal,
bad_build = _bad_build_broadcast_binary_normal,
......@@ -290,7 +293,7 @@ DivTester = make_broadcast_restet(op = div,
scalar = (rand(2, 3), rand(1, 1)),
row = (rand(2, 3), rand(1, 3)),
column = (rand(2, 3), rand(2, 1))))
DivInplaceTester = make_broadcast_restet(op = tensor._div_inplace,
DivInplaceTester = make_broadcast_restet(op = inplace.div_inplace,
expected = lambda x, y: x / y,
good = dict(same_shapes = (rand(2, 3), rand(2, 3)),
scalar = (rand(2, 3), rand(1, 1)),
......@@ -320,7 +323,7 @@ ModTester = make_broadcast_restet(op = mod,
# dtype_mixup_1 = (rand(2, 3), randint_nonzero(2, 3)),
# dtype_mixup_2 = (randint_nonzero(2, 3), rand(2, 3))),
)
ModInplaceTester = make_broadcast_restet(op = tensor._mod_inplace,
ModInplaceTester = make_broadcast_restet(op = inplace.mod_inplace,
expected = lambda x, y: x % y,
good = dict(same_shapes = (rand(2, 3), rand(2, 3)),
scalar = (rand(2, 3), rand(1, 1)),
......@@ -343,7 +346,7 @@ PowTester = make_broadcast_restet(op = pow,
row = (rand_ranged(1, 5, (2, 3)), rand_ranged(-3, 3, (1, 3))),
column = (rand_ranged(1, 5, (2, 3)), rand_ranged(-3, 3, (2, 1))))
)
PowInplaceTester = make_broadcast_restet(op = tensor._pow_inplace,
PowInplaceTester = make_broadcast_restet(op = inplace.pow_inplace,
expected = lambda x, y: x ** y,
good = dict(same_shapes = (rand_ranged(1, 5, (2, 3)), rand_ranged(-3, 3, (2, 3))),
scalar = (rand_ranged(1, 5, (2, 3)), rand_ranged(-3, 3, (1, 1))),
......@@ -364,11 +367,11 @@ _good_broadcast_unary_normal = dict(normal = (rand_ranged(-5, 5, (2, 3)),),
_grad_broadcast_unary_normal = dict(normal = (rand_ranged(-5, 5, (2, 3)),))
AbsTester = make_broadcast_restet(op = tensor._abs,
AbsTester = make_broadcast_restet(op = tensor.abs_,
expected = lambda x: abs(x),
good = _good_broadcast_unary_normal,
grad = _grad_broadcast_unary_normal)
AbsInplaceTester = make_broadcast_restet(op = tensor.__abs_inplace,
AbsInplaceTester = make_broadcast_restet(op = inplace.abs__inplace,
expected = lambda x: numpy.abs(x),
good = _good_broadcast_unary_normal,
grad = _grad_broadcast_unary_normal,
......@@ -378,7 +381,7 @@ NegTester = make_broadcast_restet(op = neg,
expected = lambda x: -x,
good = _good_broadcast_unary_normal,
grad = _grad_broadcast_unary_normal)
NegInplaceTester = make_broadcast_restet(op = tensor._neg_inplace,
NegInplaceTester = make_broadcast_restet(op = inplace.neg_inplace,
expected = lambda x: -x,
good = _good_broadcast_unary_normal,
grad = _grad_broadcast_unary_normal,
......@@ -387,7 +390,7 @@ NegInplaceTester = make_broadcast_restet(op = tensor._neg_inplace,
SgnTester = make_broadcast_restet(op = sgn,
expected = numpy.sign,
good = _good_broadcast_unary_normal)
SgnInplaceTester = make_broadcast_restet(op = tensor._sgn_inplace,
SgnInplaceTester = make_broadcast_restet(op = inplace.sgn_inplace,
expected = numpy.sign,
good = _good_broadcast_unary_normal,
inplace = True)
......@@ -396,7 +399,7 @@ SqrTester = make_broadcast_restet(op = sqr,
expected = numpy.square,
good = _good_broadcast_unary_normal,
grad = _grad_broadcast_unary_normal)
SqrInplaceTester = make_broadcast_restet(op = tensor._sqr_inplace,
SqrInplaceTester = make_broadcast_restet(op = inplace.sqr_inplace,
expected = numpy.square,
good = _good_broadcast_unary_normal,
grad = _grad_broadcast_unary_normal,
......@@ -406,7 +409,7 @@ ExpTester = make_broadcast_restet(op = exp,
expected = numpy.exp,
good = _good_broadcast_unary_normal,
grad = _grad_broadcast_unary_normal)
ExpInplaceTester = make_broadcast_restet(op = tensor._exp_inplace,
ExpInplaceTester = make_broadcast_restet(op = inplace.exp_inplace,
expected = numpy.exp,
good = _good_broadcast_unary_normal,
grad = _grad_broadcast_unary_normal,
......@@ -422,7 +425,7 @@ LogTester = make_broadcast_restet(op = log,
expected = numpy.log,
good = _good_broadcast_unary_positive,
grad = _grad_broadcast_unary_positive)
LogInplaceTester = make_broadcast_restet(op = tensor._log_inplace,
LogInplaceTester = make_broadcast_restet(op = inplace.log_inplace,
expected = numpy.log,
good = _good_broadcast_unary_positive,
grad = _grad_broadcast_unary_positive,
......@@ -432,7 +435,7 @@ Log2Tester = make_broadcast_restet(op = log2,
expected = numpy.log2,
good = _good_broadcast_unary_positive,
grad = _grad_broadcast_unary_positive)
Log2InplaceTester = make_broadcast_restet(op = tensor._log2_inplace,
Log2InplaceTester = make_broadcast_restet(op = inplace.log2_inplace,
expected = numpy.log2,
good = _good_broadcast_unary_positive,
grad = _grad_broadcast_unary_positive,
......@@ -442,7 +445,7 @@ SqrtTester = make_broadcast_restet(op = sqrt,
expected = numpy.sqrt,
good = _good_broadcast_unary_positive,
grad = _grad_broadcast_unary_positive)
SqrtInplaceTester = make_broadcast_restet(op = tensor._sqrt_inplace,
SqrtInplaceTester = make_broadcast_restet(op = inplace.sqrt_inplace,
expected = numpy.sqrt,
good = _good_broadcast_unary_positive,
grad = _grad_broadcast_unary_positive,
......@@ -460,7 +463,7 @@ SinTester = make_broadcast_restet(op = sin,
expected = numpy.sin,
good = _good_broadcast_unary_wide,
grad = _grad_broadcast_unary_wide)
SinInplaceTester = make_broadcast_restet(op = tensor._sin_inplace,
SinInplaceTester = make_broadcast_restet(op = inplace.sin_inplace,
expected = numpy.sin,
good = _good_broadcast_unary_wide,
grad = _grad_broadcast_unary_wide,
......@@ -470,7 +473,7 @@ CosTester = make_broadcast_restet(op = cos,
expected = numpy.cos,
good = _good_broadcast_unary_wide,
grad = _grad_broadcast_unary_wide)
CosInplaceTester = make_broadcast_restet(op = tensor._cos_inplace,
CosInplaceTester = make_broadcast_restet(op = inplace.cos_inplace,
expected = numpy.cos,
good = _good_broadcast_unary_wide,
grad = _grad_broadcast_unary_wide,
......@@ -482,7 +485,7 @@ TanTester = make_broadcast_restet(op = tan,
shifted = (rand_ranged(3.15, 6.28, (2, 3)),)),
grad = dict(normal = (rand_ranged(-3.14, 3.14, (2, 3)),),
shifted = (rand_ranged(3.15, 6.28, (2, 3)),)))
TanInplaceTester = make_broadcast_restet(op = tensor._tan_inplace,
TanInplaceTester = make_broadcast_restet(op = inplace.tan_inplace,
expected = numpy.tan,
good = dict(normal = (rand_ranged(-3.14, 3.14, (2, 3)),),
shifted = (rand_ranged(3.15, 6.28, (2, 3)),)),
......@@ -495,7 +498,7 @@ CoshTester = make_broadcast_restet(op = cosh,
expected = numpy.cosh,
good = _good_broadcast_unary_normal,
grad = _grad_broadcast_unary_normal)
CoshInplaceTester = make_broadcast_restet(op = tensor._cosh_inplace,
CoshInplaceTester = make_broadcast_restet(op = inplace.cosh_inplace,
expected = numpy.cosh,
good = _good_broadcast_unary_normal,
grad = _grad_broadcast_unary_normal,
......@@ -505,7 +508,7 @@ SinhTester = make_broadcast_restet(op = sinh,
expected = numpy.sinh,
good = _good_broadcast_unary_normal,
grad = _grad_broadcast_unary_normal)
SinhInplaceTester = make_broadcast_restet(op = tensor._sinh_inplace,
SinhInplaceTester = make_broadcast_restet(op = inplace.sinh_inplace,
expected = numpy.sinh,
good = _good_broadcast_unary_normal,
grad = _grad_broadcast_unary_normal,
......@@ -515,7 +518,7 @@ TanhTester = make_broadcast_restet(op = tanh,
expected = numpy.tanh,
good = _good_broadcast_unary_normal,
grad = _grad_broadcast_unary_normal)
TanhInplaceTester = make_broadcast_restet(op = tensor._tanh_inplace,
TanhInplaceTester = make_broadcast_restet(op = inplace.tanh_inplace,
expected = numpy.tanh,
good = _good_broadcast_unary_normal,
grad = _grad_broadcast_unary_normal,
......@@ -663,7 +666,7 @@ class T_transpose(unittest.TestCase):
def test0(self):
n = as_tensor(numpy.ones(()))
t = transpose(n)
self.failUnless(t.owner.op == tensor._transpose_inplace)
self.failUnless(t.owner.op == inplace.transpose_inplace)
f = function([n], t)
tval = f(n.data)
self.failUnless(tval.shape == n.data.shape)
......@@ -675,7 +678,7 @@ class T_transpose(unittest.TestCase):
def test1(self):
n = as_tensor(numpy.ones(5))
t = transpose(n)
self.failUnless(t.owner.op == tensor._transpose_inplace)
self.failUnless(t.owner.op == inplace.transpose_inplace)
f = function([n], t)
tval = f(n.data)
self.failUnless(tval.shape == n.data.shape)
......@@ -686,7 +689,7 @@ class T_transpose(unittest.TestCase):
def test2(self):
n = as_tensor(numpy.ones((5,3)))
t = transpose(n)
self.failUnless(t.owner.op == tensor._transpose_inplace)
self.failUnless(t.owner.op == inplace.transpose_inplace)
f = function([n], t)
tval = f(n.data)
self.failUnless(tval.shape == (3,5))
......@@ -697,8 +700,8 @@ class T_transpose(unittest.TestCase):
def test3(self):
"""Test transpose of tensor, inplace version"""
n = as_tensor(numpy.ones((5,3,2)))
t = tensor._transpose_inplace(n)
self.failUnless(t.owner.op == tensor._transpose_inplace)
t = inplace.transpose_inplace(n)
self.failUnless(t.owner.op == inplace.transpose_inplace)
f = function([n], t)
tval = f(n.data)
self.failUnless(tval.shape == (2,3,5))
......@@ -706,8 +709,8 @@ class T_transpose(unittest.TestCase):
tval += 55.0
self.failUnless(n.data[0,0,0] == 56.0)
def test_grad(self):
verify_grad(self, tensor._transpose_inplace, [numpy.random.rand(2, 3)])
verify_grad(self, tensor._transpose_inplace, [numpy.ones(3)])
verify_grad(self, inplace.transpose_inplace, [numpy.random.rand(2, 3)])
verify_grad(self, inplace.transpose_inplace, [numpy.ones(3)])
class T_subtensor(unittest.TestCase):
def setUp(self):
......@@ -1011,7 +1014,7 @@ class T_Join_and_Split(unittest.TestCase):
verify_grad(self, lambda a, b: join(1,a,b), [v, 2*v])
class _test_comparison(unittest.TestCase):
class test_comparison(unittest.TestCase):
def test_gt(self):
x, y = fvector(), fvector()
fn = function([x,y], x > y)
......@@ -1060,7 +1063,7 @@ class _test_comparison(unittest.TestCase):
v = fn(l, r)
self.failUnless(numpy.all(v == (l != r)), (v, (l!=r)))
class _test_bitwise(unittest.TestCase):
class test_bitwise(unittest.TestCase):
def test_or(self):
x, y = bvector(), bvector()
fn = function([x,y], x|y)
......@@ -1073,7 +1076,7 @@ class _test_bitwise(unittest.TestCase):
x, y = bvector(), bvector()
fn = function([x,y], x^y)
ix = x
ix ^= y
ix = inplace.xor_inplace(ix, y)
gn = function([x,y], ix)
l = numpy.asarray([0,0,1,1], dtype = 'int8')
r = numpy.asarray([0,1,0,1], dtype = 'int8')
......@@ -1131,7 +1134,7 @@ class T_exp(unittest.TestCase):
numpy.asarray([[ 1.5089518 , 1.48439076, -4.7820262 ],
[ 2.04832468, 0.50791564, -1.58892269]])])
def test_grad_1(self):
verify_grad(self, tensor._exp_inplace, [
verify_grad(self, inplace.exp_inplace, [
numpy.asarray([[ 1.5089518 , 1.48439076, -4.7820262 ],
[ 2.04832468, 0.50791564, -1.58892269]])])
......@@ -1299,7 +1302,7 @@ class T_exp(unittest.TestCase):
# def test_col(self):
# verify_grad(self, Pow, [numpy.random.rand(3, 5), numpy.random.rand(3, 1)])
class _testCase_matinv(unittest.TestCase):
class test_matinv(unittest.TestCase):
def setUp(self):
numpy.random.seed(1)
......@@ -1499,7 +1502,7 @@ class t_gemm(unittest.TestCase):
Z = as_tensor(self.rand(2,2))
A = as_tensor(self.rand(2,2))
try:
gemm(Z, 1.0, A, tensor._transpose_inplace(Z), 1.0)
gemm(Z, 1.0, A, inplace.transpose_inplace(Z), 1.0)
except ValueError, e:
if e[0] == Gemm.E_z_uniq:
return
......@@ -1509,7 +1512,7 @@ class t_gemm(unittest.TestCase):
Z = as_tensor(self.rand(2,2))
A = as_tensor(self.rand(2,2))
try:
gemm(Z, 1.0, tensor._transpose_inplace(Z), A, 1.0)
gemm(Z, 1.0, inplace.transpose_inplace(Z), A, 1.0)
except ValueError, e:
if e[0] == Gemm.E_z_uniq:
return
......@@ -1739,7 +1742,7 @@ class T_tensorfromscalar(unittest.TestCase):
# self.failUnless(t.data is not tt.data)
class _test_grad(unittest.TestCase):
class test_grad(unittest.TestCase):
class O(gof.op.Op):
def __init__(self):
self.gval0 = scalar('e')
......@@ -1753,13 +1756,13 @@ class _test_grad(unittest.TestCase):
def test_1param(self):
"""grad: Test passing a single result param"""
o = _test_grad.O()
o = test_grad.O()
a1 = o.make_node()
self.failUnless(o.gval0 is grad(a1.outputs[0], a1.inputs[0]))
def test_Nparam(self):
"""grad: Test passing multiple result params"""
o = _test_grad.O()
o = test_grad.O()
a1 = o.make_node()
g0,g1 = grad(a1.outputs[0], a1.inputs)
self.failUnless(o.gval0 is g0)
......@@ -1767,7 +1770,7 @@ class _test_grad(unittest.TestCase):
def test_1None_rval(self):
"""grad: Test returning a single None from grad"""
o = _test_grad.O()
o = test_grad.O()
a1 = o.make_node()
g = grad(a1.outputs[0], a1.outputs[1])
self.failUnless(isinstance(g, TensorConstant))
......@@ -1780,7 +1783,7 @@ class _test_grad(unittest.TestCase):
def test_NNone_rval(self):
"""grad: Test returning some Nones from grad"""
o = _test_grad.O()
o = test_grad.O()
a1 = o.make_node()
g0,g1,g2 = grad(a1.outputs[0], a1.inputs + [scalar('z')])
self.failUnless(o.gval0 is g0)
......
theano/tests/_test_gradient.py → theano/tests/test_gradient.py
浏览文件 @ 11faef91
......@@ -9,7 +9,7 @@ from theano import gof
from theano.gradient import *
from theano import gradient
class _test_grad_sources_inputs(unittest.TestCase):
class test_grad_sources_inputs(unittest.TestCase):
def test_retNone1(self):
"""Test that it is not ok to return None from op.grad()"""
class retNone(gof.op.Op):
......
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