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提交 1029066e authored 作者: Frédéric Bastien's avatar Frédéric Bastien 提交者： GitHub
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Merge pull request #5957 from notoraptor/op-params-tensor-corr3d

Wrap Op params for theano.tensor.nnet.corr3d.BaseCorr3dMM and subclasses.
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theano/tensor/nnet/corr3d.py
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......@@ -7,6 +7,8 @@ from six import integer_types
import theano
from theano import Apply
from theano import gof
from theano.gof import ParamsType, EnumList
from theano.scalar import int64
from theano.tensor import as_tensor_variable, TensorType
from theano.tensor.nnet.abstract_conv import get_conv_output_shape
from theano.tensor import blas_headers
......@@ -19,6 +21,16 @@ class BaseCorr3dMM(gof.OpenMPOp):
"""
Base class for `Corr3dMM`, `Corr3dMM_gradWeights` and
`Corr3dMM_gradInputs`. Cannot be used directly.
Every sub-class must define internal attribute ``_direction`` out of __init__().
``_direction`` must take one of following values:
- "forward" to correlate bottom with weights and store results in top.
- "backprop weights" to do a valid convolution of bottom with top
(swapping the first two dimensions) and store results in weights.
- "backprop inputs" to do a full convolution of top with weights
(swapping the first two dimensions) and store results in bottom.
Parameters
----------
border_mode : {'valid', 'full', 'half'}
......@@ -32,6 +44,15 @@ class BaseCorr3dMM(gof.OpenMPOp):
check_broadcast = False
__props__ = ('border_mode', 'subsample', 'filter_dilation')
_direction = None
params_type = ParamsType(direction=EnumList(('DIRECTION_FORWARD', 'forward'), # 0
('DIRECTION_BACKPROP_WEIGHTS', 'backprop weights'), # 1
('DIRECTION_BACKPROP_INPUTS', 'backprop inputs')), # 2
dH=int64, dW=int64, dD=int64,
dilH=int64, dilW=int64, dilD=int64,
padH=int64, padW=int64, padD=int64)
def __init__(self, border_mode="valid", subsample=(1, 1, 1),
filter_dilation=(1, 1, 1), openmp=None):
super(BaseCorr3dMM, self).__init__(openmp=openmp)
......@@ -73,11 +94,37 @@ class BaseCorr3dMM(gof.OpenMPOp):
else:
self.blas_type = ''
if self._direction not in ["forward", "backprop weights", "backprop inputs"]:
raise ValueError("_direction must be one of 'forward', "
"'backprop weights', 'backprop inputs'")
@property
def pad(self):
if self.border_mode != 'valid':
if self.border_mode == "half":
return (-1, -1, -1)
elif self.border_mode == "full":
return (-2, -2, -2)
elif isinstance(self.border_mode, tuple):
return self.border_mode
return (0, 0, 0)
else:
assert self.border_mode == "valid"
return (0, 0, 0)
# Direction should be converted to real enum value,
# as it is compared to integer later in c_code_helper().
direction = property(lambda self: self.params_type.enum_from_alias(self._direction))
dH = property(lambda self: self.subsample[0])
dW = property(lambda self: self.subsample[1])
dD = property(lambda self: self.subsample[2])
dilH = property(lambda self: self.filter_dilation[0])
dilW = property(lambda self: self.filter_dilation[1])
dilD = property(lambda self: self.filter_dilation[2])
padH = property(lambda self: self.pad[0])
padW = property(lambda self: self.pad[1])
padD = property(lambda self: self.pad[2])
def __str__(self):
return '%s{%s, %s, %s}' % (
......@@ -123,7 +170,7 @@ class BaseCorr3dMM(gof.OpenMPOp):
def c_code_cache_version(self):
# raise this whenever modifying any of the support_code_files
return (5, self.openmp, blas_header_version())
return (7, self.openmp, blas_header_version())
def c_support_code_apply(self, node, nodename):
# REMEMBER TO RAISE c_code_cache_version when changing any of
......@@ -173,7 +220,7 @@ class BaseCorr3dMM(gof.OpenMPOp):
final_code += code
return final_code % sub
def c_code_helper(self, bottom, weights, top, direction, sub,
def c_code_helper(self, bottom, weights, top, sub,
height=None, width=None, depth=None):
"""
This generates the C code for Corr3dMM (direction="forward"),
......@@ -188,12 +235,6 @@ class BaseCorr3dMM(gof.OpenMPOp):
or the gradient of the filters in backprop wrt. weights
:param top: Variable name of the output images / feature maps in the
forward pass, or the gradient of the outputs in the backprop passes
:param direction: "forward" to correlate bottom with weights and store
results in top,
"backprop weights" to do a valid convolution of bottom with top
(swapping the first two dimensions) and store results in weights,
and "backprop inputs" to do a full convolution of top with weights
(swapping the first two dimensions) and store results in bottom.
:param sub: Dictionary of substitutions useable to help generating the
C code.
:param height: If self.subsample[0] != 1, a variable giving the height
......@@ -215,72 +256,65 @@ class BaseCorr3dMM(gof.OpenMPOp):
If self.border_mode == 'half', a variable giving the depth of the
filters for direction="backprop weights". Ignored otherwise.
"""
dH, dW, dD = self.subsample
dilH, dilW, dilD = self.filter_dilation
if self.border_mode == "half":
padH = padW = padD = -1
elif self.border_mode == "full":
padH = padW = padD = -2
elif isinstance(self.border_mode, tuple):
padH, padW, padD = self.border_mode
else:
assert self.border_mode == "valid"
padH = padW = padD = 0
if direction == "forward":
direction = 0
out = top
elif direction == "backprop weights":
direction = 1
out = weights
elif direction == "backprop inputs":
direction = 2
out = bottom
else:
raise ValueError("direction must be one of 'forward', "
"'backprop weights', 'backprop inputs'")
# When subsampling, we cannot unambiguously infer the height and width
# of bottom and weights from top, so we require them to be given.
# Similarly, when border_mode="half", we cannot infer the weight size.
if height:
height = '(*(npy_int64 *)(PyArray_DATA(%s)))' % height
else:
if ((direction != 0) and (dH != 1)) or ((direction == 1) and (padH == -1)):
if ((self.direction != 0) and (self.dH != 1)) or ((self.direction == 1) and (self.padH == -1)):
raise ValueError("height must be given for backprop with vertical sampling or border_mode='half'")
height = '-1'
if width:
width = '(*(npy_int64 *)(PyArray_DATA(%s)))' % width
else:
if ((direction != 0) and (dW != 1)) or ((direction == 1) and (padW == -1)):
if ((self.direction != 0) and (self.dW != 1)) or ((self.direction == 1) and (self.padW == -1)):
raise ValueError("width must be given for backprop with horizontal sampling or border_mode='half'")
width = '-1'
if depth:
depth = '(*(npy_int64 *)(PyArray_DATA(%s)))' % depth
else:
if ((direction != 0) and (dD != 1)) or ((direction == 1) and (padD == -1)):
if ((self.direction != 0) and (self.dD != 1)) or ((self.direction == 1) and (self.padD == -1)):
raise ValueError("depth must be given for backprop with depth sampling or border_mode='half'")
depth = '-1'
sub = sub.copy()
sub.update(locals())
return """
// Mandatory args
int direction = %(direction)s; // forward, bprop weights, bprop inputs
int direction = %(params)s->direction; // forward, bprop weights, bprop inputs
// Optional args
int dH = %(dH)s;
int dW = %(dW)s;
int dD = %(dD)s;
int dilH = %(dilH)s;
int dilW = %(dilW)s;
int dilD = %(dilD)s;
int padH = %(padH)s;
int padW = %(padW)s;
int padD = %(padD)s;
int dH = %(params)s->dH;
int dW = %(params)s->dW;
int dD = %(params)s->dD;
int dilH = %(params)s->dilH;
int dilW = %(params)s->dilW;
int dilD = %(params)s->dilD;
int padH = %(params)s->padH;
int padW = %(params)s->padW;
int padD = %(params)s->padD;
PyArrayObject * bottom = %(bottom)s;
PyArrayObject * weights = %(weights)s;
PyArrayObject * top = %(top)s;
PyArrayObject * out2 = NULL;
PyArrayObject **out = NULL;
switch(%(params)s->direction) {
case DIRECTION_FORWARD:
out = &%(top)s;
break;
case DIRECTION_BACKPROP_WEIGHTS:
out = &%(weights)s;
break;
case DIRECTION_BACKPROP_INPUTS:
out = &%(bottom)s;
break;
default:
PyErr_SetString(PyExc_ValueError, "CPU Corr3dMM: Invalid direction.");
{%(fail)s}
break;
}
// Obtain or infer kernel width, height and depth
// (we need to know it early to be able to handle auto-padding)
......@@ -449,16 +483,16 @@ class BaseCorr3dMM(gof.OpenMPOp):
// Prepare output array
int typenum;
if ( !(%(out)s
&& PyArray_NDIM(%(out)s)==4
&& PyArray_IS_C_CONTIGUOUS(%(out)s)
&& PyArray_DIMS(%(out)s)[0]==out_dim[0]
&& PyArray_DIMS(%(out)s)[1]==out_dim[1]
&& PyArray_DIMS(%(out)s)[2]==out_dim[2]
&& PyArray_DIMS(%(out)s)[3]==out_dim[3]
&& PyArray_DIMS(%(out)s)[4]==out_dim[4]))
if ( !(*out
&& PyArray_NDIM(*out)==4
&& PyArray_IS_C_CONTIGUOUS(*out)
&& PyArray_DIMS(*out)[0]==out_dim[0]
&& PyArray_DIMS(*out)[1]==out_dim[1]
&& PyArray_DIMS(*out)[2]==out_dim[2]
&& PyArray_DIMS(*out)[3]==out_dim[3]
&& PyArray_DIMS(*out)[4]==out_dim[4]))
{
Py_XDECREF(%(out)s);
Py_XDECREF(*out);
if (direction != 1) {
typenum = PyArray_TYPE(weights);
}
......@@ -466,11 +500,11 @@ class BaseCorr3dMM(gof.OpenMPOp):
typenum = PyArray_TYPE(bottom);
}
//Change to PyArray_ZEROS which is faster than PyArray_EMPTY.
%(out)s = (PyArrayObject*)PyArray_ZEROS(5,
*out = (PyArrayObject*)PyArray_ZEROS(5,
out_dim,
typenum,
0);
if (NULL == %(out)s)
if (NULL == *out)
{
PyErr_Format(PyExc_RuntimeError,
"BaseCorr3dMM: Failed to allocate output of %%lld x %%lld x %%lld x %%lld x %%lld",
......@@ -486,9 +520,11 @@ class BaseCorr3dMM(gof.OpenMPOp):
if (out2==NULL){
%(fail)s
}
assert (out2 == %(out)s);
assert (out2 == *out);
""" % sub
""" % dict(bottom=bottom, weights=weights, top=top,
height=height, width=width, depth=depth,
fail=sub['fail'], params=sub['params'])
class Corr3dMM(BaseCorr3dMM):
......@@ -519,6 +555,8 @@ class Corr3dMM(BaseCorr3dMM):
"""
_direction = "forward"
def make_node(self, img, kern):
img = as_tensor_variable(img)
kern = as_tensor_variable(kern)
......@@ -547,8 +585,7 @@ class Corr3dMM(BaseCorr3dMM):
def c_code(self, node, nodename, inp, out_, sub):
bottom, weights = inp
top, = out_
direction = "forward"
return super(Corr3dMM, self).c_code_helper(bottom, weights, top, direction, sub)
return super(Corr3dMM, self).c_code_helper(bottom, weights, top, sub)
def grad(self, inp, grads):
bottom, weights = inp
......@@ -576,6 +613,8 @@ class Corr3dMM_gradWeights(BaseCorr3dMM):
"""
_direction = "backprop weights"
def make_node(self, img, topgrad, shape=None):
img = as_tensor_variable(img)
topgrad = as_tensor_variable(topgrad)
......@@ -643,9 +682,8 @@ class Corr3dMM_gradWeights(BaseCorr3dMM):
bottom, top = inp[:2]
height, width, depth = inp[2:] or (None, None, None)
weights, = out_
direction = "backprop weights"
return super(Corr3dMM_gradWeights,
self).c_code_helper(bottom, weights, top, direction,
self).c_code_helper(bottom, weights, top,
sub, height, width, depth)
def grad(self, inp, grads):
......@@ -681,6 +719,8 @@ class Corr3dMM_gradInputs(BaseCorr3dMM):
"""
_direction = "backprop inputs"
def make_node(self, kern, topgrad, shape=None):
kern = as_tensor_variable(kern)
topgrad = as_tensor_variable(topgrad)
......@@ -758,9 +798,8 @@ class Corr3dMM_gradInputs(BaseCorr3dMM):
weights, top = inp[:2]
height, width, depth = inp[2:] or (None, None, None)
bottom, = out_
direction = "backprop inputs"
return super(Corr3dMM_gradInputs,
self).c_code_helper(bottom, weights, top, direction, sub,
self).c_code_helper(bottom, weights, top, sub,
height, width, depth)
def grad(self, inp, grads):
......
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