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Commit 2d1b7752 by Ting PAN
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Disable sharing gradients on shape ops

1 parent 7bc8fb22
Inline Side-by-side
Showing with 287 additions and 247 deletions
Dragon/include/operators/ndarray/concat_op.h
......@@ -31,12 +31,13 @@ class ConcatOp : public Operator<Context> {
template <class Context>
class ConcatGradientOp : public Operator<Context> {
public:
ConcatGradientOp(const OperatorDef& op_def, Workspace* ws)
ConcatGradientOp(const OperatorDef& op_def, Workspace* ws)
: Operator<Context>(op_def, ws),
axis(OperatorBase::GetSingleArg<int>("axis", 1)),
nin(OperatorBase::GetSingleArg<int>("num_input", 1)) {}
nin(OperatorBase::GetSingleArg<int>("num_input", 1)) {
DISABLE_SHARE_GRADIENT;
}
void ShareGradient() override;
void RunOnDevice() override;
template <typename T> void RunWithType();
......
Dragon/include/operators/ndarray/crop_op.h
......@@ -46,7 +46,9 @@ class CropGradientOp final : public Operator<Context > {
start_axis(OperatorBase::GetSingleArg<int>("start_axis", -1)),
offsets(OperatorBase::GetRepeatedArg<int>("offsets")),
shape(OperatorBase::GetRepeatedArg<int>("shape")),
shape_like(OperatorBase::GetSingleArg<string>("shape_like", "")) {}
shape_like(OperatorBase::GetSingleArg<string>("shape_like", "")) {
DISABLE_SHARE_GRADIENT;
}
void Setup();
void RunOnDevice() override;
......
Dragon/include/operators/ndarray/expand_dims_op.h
......@@ -28,7 +28,9 @@ template <class Context>
class ExpandDimsGradientOp final : public Operator<Context> {
public:
ExpandDimsGradientOp(const OperatorDef& op_def, Workspace* ws)
: Operator<Context>(op_def, ws) {}
: Operator<Context>(op_def, ws) {
DISABLE_SHARE_GRADIENT;
}
void RunOnDevice() override;
};
......
Dragon/include/operators/ndarray/flatten_op.h
......@@ -32,7 +32,9 @@ template <class Context>
class FlattenGradientOp final : public Operator<Context> {
public:
FlattenGradientOp(const OperatorDef& op_def, Workspace* ws)
: Operator<Context>(op_def, ws) {}
: Operator<Context>(op_def, ws) {
DISABLE_SHARE_GRADIENT;
}
void RunOnDevice() override;
};
......
Dragon/include/operators/ndarray/pad_op.h
......@@ -63,6 +63,7 @@ class PadGradientOp final : public Operator<Context> {
}
std::sort(process_axes.begin(), process_axes.end());
std::reverse(process_axes.begin(), process_axes.end());
DISABLE_SHARE_GRADIENT;
}
void RunOnDevice() override;
......
Dragon/include/operators/ndarray/random_pick_op.h
......@@ -34,7 +34,9 @@ class RandomPickGradientOp final : public Operator<Context> {
public:
RandomPickGradientOp(const OperatorDef& op_def, Workspace* ws)
: Operator<Context>(op_def, ws),
axis(OperatorBase::GetSingleArg<int>("axis", 0)) {}
axis(OperatorBase::GetSingleArg<int>("axis", 0)) {
DISABLE_SHARE_GRADIENT;
}
void RunOnDevice() override;
template <typename T> void RunWithType();
......
Dragon/include/operators/ndarray/reshape_op.h
......@@ -31,7 +31,9 @@ template <class Context>
class ReshapeGradientOp final : public Operator<Context> {
public:
ReshapeGradientOp(const OperatorDef& op_def, Workspace* ws)
: Operator<Context>(op_def, ws) {}
: Operator<Context>(op_def, ws) {
DISABLE_SHARE_GRADIENT;
}
void RunOnDevice() override;
};
......
Dragon/include/operators/ndarray/tile_op.h
......@@ -44,6 +44,7 @@ class TileGradientOp : public Operator<Context> {
process_axes.push_back({ multiples[i], i });
std::sort(process_axes.begin(), process_axes.end());
std::reverse(process_axes.begin(), process_axes.end());
DISABLE_SHARE_GRADIENT;
}
void RunOnDevice() override;
......
Dragon/include/operators/vision/roi_align_op.h
......@@ -29,7 +29,7 @@ class ROIAlignOp : public Operator<Context> {
protected:
int pool_h, pool_w;
float spatial_scale;
Tensor* mask;
Tensor* mask_h, *mask_w;
};
template <class Context>
......@@ -50,7 +50,7 @@ class ROIAlignGradientOp : public Operator<Context> {
protected:
int pool_h, pool_w;
float spatial_scale;
Tensor* mask;
Tensor* mask_h, *mask_w;
};
} // namespace dragon
......
Dragon/include/utils/op_kernel.h
......@@ -813,7 +813,8 @@ void ROIAlign(const float spatial_scale,
const int pool_w,
Tensor* x,
Tensor* roi,
Tensor* mask,
Tensor* mask_h,
Tensor* mask_w,
Tensor* y);
template <typename T, class Context>
......@@ -822,7 +823,8 @@ void ROIAlignGrad(const float spatial_scale,
const int pool_w,
Tensor* dy,
Tensor* roi,
Tensor* mask,
Tensor* mask_h,
Tensor* mask_w,
Tensor* dx);
} // namespace kernel
......
Dragon/python/dragon/vm/caffe/layers/__init__.py
......@@ -21,6 +21,7 @@ from .neuron import ReLULayer, \
ELULayer, \
SELULayer, \
DropoutLayer, \
SigmoidLayer, \
TanHLayer, \
PowerLayer
......@@ -53,6 +54,7 @@ from .common import InnerProductLayer, \
NormalizeLayer, \
InstanceNormLayer, \
TileLayer, \
ReductionLayer, \
ExpandDimsLayer, \
ProposalLayer, \
DenseConcatLayer
\ No newline at end of file
Dragon/python/dragon/vm/caffe/layers/common.py
......@@ -553,6 +553,32 @@ class TileLayer(Layer):
return ops.Tile(input, **self._param)
class ReductionLayer(Layer):
"""The extended implementation of ``ReductionLayer``.
Parameters
----------
operation : caffe_pb2.ReductionOp
The operation. Refer `ReductionParameter.operation`_.
axis : int
The axis to to reduce. Refer `ReductionParameter.axis`_.
"""
def __init__(self, LayerParameter):
super(ReductionLayer, self).__init__(LayerParameter)
param = LayerParameter.reduction_param
if param.axis < 0:
if param.axis != -1:
raise ValueError('The negative axis can only be -1(reduce all).')
self._param = {'operation': {1: 'SUM', 4: 'MEAN'}[param.operation],
'axis': param.axis}
def Setup(self, bottom):
super(ReductionLayer, self).Setup(bottom)
input = bottom[0] if isinstance(bottom, list) else bottom
return ops.Reduce(input, **self._param)
class ExpandDimsLayer(Layer):
"""The implementation of ``ExpandDimsLayer``.
......
Dragon/python/dragon/vm/caffe/layers/loss.py
......@@ -27,7 +27,7 @@ class SoftmaxWithLossLayer(Layer):
super(SoftmaxWithLossLayer, self).__init__(LayerParameter)
param = LayerParameter.loss_param
softmax_param = LayerParameter.softmax_param
norm_mode = {0: 'FULL', 1: 'VALID', 2: 'BATCH_SIZE', 3: 'NONE'}
norm_mode = {0: 'FULL', 1: 'VALID', 2: 'BATCH_SIZE', 3: 'NONE', 4: 'UNIT'}
normalization = 'VALID'
if param.HasField('normalize'):
if not param.normalize: normalization = 'BATCH_SIZE'
......@@ -57,7 +57,7 @@ class SigmoidCrossEntropyLossLayer(Layer):
def __init__(self, LayerParameter):
super(SigmoidCrossEntropyLossLayer, self).__init__(LayerParameter)
param = LayerParameter.loss_param
norm_mode = {0: 'FULL', 1: 'BATCH_SIZE', 2: 'BATCH_SIZE', 3: 'NONE'}
norm_mode = {0: 'FULL', 1: 'BATCH_SIZE', 2: 'BATCH_SIZE', 3: 'NONE', 4: 'UNIT'}
normalization = 'BATCH_SIZE'
if param.HasField('normalize'):
if param.normalize: normalization = 'FULL'
......@@ -157,7 +157,7 @@ class SoftmaxWithFocalLossLayer(Layer):
param = LayerParameter.loss_param
softmax_param = LayerParameter.softmax_param
focal_loss_param = LayerParameter.focal_loss_param
norm_mode = {0: 'FULL', 1: 'VALID', 2: 'BATCH_SIZE', 3: 'NONE'}
norm_mode = {0: 'FULL', 1: 'VALID', 2: 'BATCH_SIZE', 3: 'NONE', 4: 'UNIT'}
normalization = 'VALID'
if param.HasField('normalize'):
if not param.normalize: normalization = 'BATCH_SIZE'
......@@ -174,4 +174,4 @@ class SoftmaxWithFocalLossLayer(Layer):
super(SoftmaxWithFocalLossLayer, self).Setup(bottom)
loss = ops.SparseSoftmaxFocalLoss(bottom, **self._param)
if self._loss_weight is not None: loss *= self._loss_weight
return loss
return loss
\ No newline at end of file
Dragon/python/dragon/vm/caffe/net.py
......@@ -215,8 +215,13 @@ class Net(object):
if len(LayerParameter.loss_weight) == 0:
LayerParameter.loss_weight.extend([1.0])
for idx, loss_weight in enumerate(LayerParameter.loss_weight):
if loss_weight <= 0: continue
self._costs.append(self.blobs[LayerParameter.top[idx]].data)
if loss_weight <= 0: continue
self._costs.append(self.blobs[LayerParameter.top[idx]].data)
else:
if len(LayerParameter.loss_weight) != 0:
for idx, loss_weight in enumerate(LayerParameter.loss_weight):
if loss_weight <= 0: continue
self._costs.append(self.blobs[LayerParameter.top[idx]].data)
if self._phase != 'TRAIN': return
......
Dragon/python/dragon/vm/caffe/proto/caffe.proto
......@@ -473,6 +473,8 @@ message LossParameter {
BATCH_SIZE = 2;
// Do not normalize the loss.
NONE = 3;
// Do not reduce the loss.
UNIT = 4;
}
optional NormalizationMode normalization = 3 [default = VALID];
// Deprecated. Ignored if normalization is specified. If normalization
......
Dragon/python/dragon/vm/caffe/proto/caffe_pb2.py
......@@ -19,7 +19,7 @@ _sym_db = _symbol_database.Default()
DESCRIPTOR = _descriptor.FileDescriptor(
name='caffe.proto',
package='caffe',
serialized_pb=_b('\n\x0b\x63\x61\x66\x66\x65.proto\x12\x05\x63\x61\x66\x66\x65\"\x1c\n\tBlobShape\x12\x0f\n\x03\x64im\x18\x01 \x03(\x03\x42\x02\x10\x01\"\xcc\x01\n\tBlobProto\x12\x1f\n\x05shape\x18\x07 \x01(\x0b\x32\x10.caffe.BlobShape\x12\x10\n\x04\x64\x61ta\x18\x05 \x03(\x02\x42\x02\x10\x01\x12\x10\n\x04\x64iff\x18\x06 \x03(\x02\x42\x02\x10\x01\x12\x17\n\x0b\x64ouble_data\x18\x08 \x03(\x01\x42\x02\x10\x01\x12\x17\n\x0b\x64ouble_diff\x18\t \x03(\x01\x42\x02\x10\x01\x12\x0e\n\x03num\x18\x01 \x01(\x05:\x01\x30\x12\x13\n\x08\x63hannels\x18\x02 \x01(\x05:\x01\x30\x12\x11\n\x06height\x18\x03 \x01(\x05:\x01\x30\x12\x10\n\x05width\x18\x04 \x01(\x05:\x01\x30\"2\n\x0f\x42lobProtoVector\x12\x1f\n\x05\x62lobs\x18\x01 \x03(\x0b\x32\x10.caffe.BlobProto\"\x81\x01\n\x05\x44\x61tum\x12\x10\n\x08\x63hannels\x18\x01 \x01(\x05\x12\x0e\n\x06height\x18\x02 \x01(\x05\x12\r\n\x05width\x18\x03 \x01(\x05\x12\x0c\n\x04\x64\x61ta\x18\x04 \x01(\x0c\x12\r\n\x05label\x18\x05 \x01(\x05\x12\x12\n\nfloat_data\x18\x06 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)
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
......@@ -40,8 +40,8 @@ _PHASE = _descriptor.EnumDescriptor(
],
containing_type=None,
options=None,
serialized_start=17298,
serialized_end=17326,
serialized_start=17308,
serialized_end=17336,
)
_sym_db.RegisterEnumDescriptor(_PHASE)
......@@ -202,11 +202,15 @@ _LOSSPARAMETER_NORMALIZATIONMODE = _descriptor.EnumDescriptor(
name='NONE', index=3, number=3,
options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='UNIT', index=4, number=4,
options=None,
type=None),
],
containing_type=None,
options=None,
serialized_start=6478,
serialized_end=6544,
serialized_end=6554,
)
_sym_db.RegisterEnumDescriptor(_LOSSPARAMETER_NORMALIZATIONMODE)
......@@ -231,8 +235,8 @@ _CONVOLUTIONPARAMETER_ENGINE = _descriptor.EnumDescriptor(
],
containing_type=None,
options=None,
serialized_start=7507,
serialized_end=7550,
serialized_start=7517,
serialized_end=7560,
)
_sym_db.RegisterEnumDescriptor(_CONVOLUTIONPARAMETER_ENGINE)
......@@ -253,8 +257,8 @@ _DATAPARAMETER_DB = _descriptor.EnumDescriptor(
],
containing_type=None,
options=None,
serialized_start=7868,
serialized_end=7895,
serialized_start=7878,
serialized_end=7905,
)
_sym_db.RegisterEnumDescriptor(_DATAPARAMETER_DB)
......@@ -279,8 +283,8 @@ _ELTWISEPARAMETER_ELTWISEOP = _descriptor.EnumDescriptor(
],
containing_type=None,
options=None,
serialized_start=8262,
serialized_end=8301,
serialized_start=8272,
serialized_end=8311,
)
_sym_db.RegisterEnumDescriptor(_ELTWISEPARAMETER_ELTWISEOP)
......@@ -301,8 +305,8 @@ _HINGELOSSPARAMETER_NORM = _descriptor.EnumDescriptor(
],
containing_type=None,
options=None,
serialized_start=8836,
serialized_end=8858,
serialized_start=8846,
serialized_end=8868,
)
_sym_db.RegisterEnumDescriptor(_HINGELOSSPARAMETER_NORM)
......@@ -323,8 +327,8 @@ _LRNPARAMETER_NORMREGION = _descriptor.EnumDescriptor(
],
containing_type=None,
options=None,
serialized_start=9725,
serialized_end=9778,
serialized_start=9735,
serialized_end=9788,
)
_sym_db.RegisterEnumDescriptor(_LRNPARAMETER_NORMREGION)
......@@ -349,8 +353,8 @@ _LRNPARAMETER_ENGINE = _descriptor.EnumDescriptor(
],
containing_type=None,
options=None,
serialized_start=7507,
serialized_end=7550,
serialized_start=7517,
serialized_end=7560,
)
_sym_db.RegisterEnumDescriptor(_LRNPARAMETER_ENGINE)
......@@ -371,8 +375,8 @@ _MEMORYDATAPARAMETER_DATATYPE = _descriptor.EnumDescriptor(
],
containing_type=None,
options=None,
serialized_start=9979,
serialized_end=10015,
serialized_start=9989,
serialized_end=10025,
)
_sym_db.RegisterEnumDescriptor(_MEMORYDATAPARAMETER_DATATYPE)
......@@ -397,8 +401,8 @@ _POOLINGPARAMETER_POOLMETHOD = _descriptor.EnumDescriptor(
],
containing_type=None,
options=None,
serialized_start=10503,
serialized_end=10549,
serialized_start=10513,
serialized_end=10559,
)
_sym_db.RegisterEnumDescriptor(_POOLINGPARAMETER_POOLMETHOD)
......@@ -423,8 +427,8 @@ _POOLINGPARAMETER_ENGINE = _descriptor.EnumDescriptor(
],
containing_type=None,
options=None,
serialized_start=7507,
serialized_end=7550,
serialized_start=7517,
serialized_end=7560,
)
_sym_db.RegisterEnumDescriptor(_POOLINGPARAMETER_ENGINE)
......@@ -453,8 +457,8 @@ _REDUCTIONPARAMETER_REDUCTIONOP = _descriptor.EnumDescriptor(
],
containing_type=None,
options=None,
serialized_start=10985,
serialized_end=11038,
serialized_start=10995,
serialized_end=11048,
)
_sym_db.RegisterEnumDescriptor(_REDUCTIONPARAMETER_REDUCTIONOP)
......@@ -479,8 +483,8 @@ _RELUPARAMETER_ENGINE = _descriptor.EnumDescriptor(
],
containing_type=None,
options=None,
serialized_start=7507,
serialized_end=7550,
serialized_start=7517,
serialized_end=7560,
)
_sym_db.RegisterEnumDescriptor(_RELUPARAMETER_ENGINE)
......@@ -505,8 +509,8 @@ _SIGMOIDPARAMETER_ENGINE = _descriptor.EnumDescriptor(
],
containing_type=None,
options=None,
serialized_start=7507,
serialized_end=7550,
serialized_start=7517,
serialized_end=7560,
)
_sym_db.RegisterEnumDescriptor(_SIGMOIDPARAMETER_ENGINE)
......@@ -531,8 +535,8 @@ _SOFTMAXPARAMETER_ENGINE = _descriptor.EnumDescriptor(
],
containing_type=None,
options=None,
serialized_start=7507,
serialized_end=7550,
serialized_start=7517,
serialized_end=7560,
)
_sym_db.RegisterEnumDescriptor(_SOFTMAXPARAMETER_ENGINE)
......@@ -557,8 +561,8 @@ _TANHPARAMETER_ENGINE = _descriptor.EnumDescriptor(
],
containing_type=None,
options=None,
serialized_start=7507,
serialized_end=7550,
serialized_start=7517,
serialized_end=7560,
)
_sym_db.RegisterEnumDescriptor(_TANHPARAMETER_ENGINE)
......@@ -583,8 +587,8 @@ _SPPPARAMETER_POOLMETHOD = _descriptor.EnumDescriptor(
],
containing_type=None,
options=None,
serialized_start=10503,
serialized_end=10549,
serialized_start=10513,
serialized_end=10559,
)
_sym_db.RegisterEnumDescriptor(_SPPPARAMETER_POOLMETHOD)
......@@ -609,8 +613,8 @@ _SPPPARAMETER_ENGINE = _descriptor.EnumDescriptor(
],
containing_type=None,
options=None,
serialized_start=7507,
serialized_end=7550,
serialized_start=7517,
serialized_end=7560,
)
_sym_db.RegisterEnumDescriptor(_SPPPARAMETER_ENGINE)
......@@ -783,8 +787,8 @@ _V1LAYERPARAMETER_LAYERTYPE = _descriptor.EnumDescriptor(
],
containing_type=None,
options=None,
serialized_start=14477,
serialized_end=15077,
serialized_start=14487,
serialized_end=15087,
)
_sym_db.RegisterEnumDescriptor(_V1LAYERPARAMETER_LAYERTYPE)
......@@ -831,8 +835,8 @@ _V0LAYERPARAMETER_POOLMETHOD = _descriptor.EnumDescriptor(
],
containing_type=None,
options=None,
serialized_start=10503,
serialized_end=10549,
serialized_start=10513,
serialized_end=10559,
)
_sym_db.RegisterEnumDescriptor(_V0LAYERPARAMETER_POOLMETHOD)
......@@ -2436,7 +2440,7 @@ _LOSSPARAMETER = _descriptor.Descriptor(
oneofs=[
],
serialized_start=6309,
serialized_end=6544,
serialized_end=6554,
)
......@@ -2479,8 +2483,8 @@ _ACCURACYPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=6546,
serialized_end=6622,
serialized_start=6556,
serialized_end=6632,
)
......@@ -2523,8 +2527,8 @@ _ARGMAXPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=6624,
serialized_end=6701,
serialized_start=6634,
serialized_end=6711,
)
......@@ -2560,8 +2564,8 @@ _CONCATPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=6703,
serialized_end=6760,
serialized_start=6713,
serialized_end=6770,
)
......@@ -2604,8 +2608,8 @@ _BATCHNORMPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=6762,
serialized_end=6866,
serialized_start=6772,
serialized_end=6876,
)
......@@ -2648,8 +2652,8 @@ _BIASPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=6868,
serialized_end=6961,
serialized_start=6878,
serialized_end=6971,
)
......@@ -2685,8 +2689,8 @@ _CONTRASTIVELOSSPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=6963,
serialized_end=7039,
serialized_start=6973,
serialized_end=7049,
)
......@@ -2835,8 +2839,8 @@ _CONVOLUTIONPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=7042,
serialized_end=7550,
serialized_start=7052,
serialized_end=7560,
)
......@@ -2872,8 +2876,8 @@ _CROPPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=7552,
serialized_end=7600,
serialized_start=7562,
serialized_end=7610,
)
......@@ -2966,8 +2970,8 @@ _DATAPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=7603,
serialized_end=7895,
serialized_start=7613,
serialized_end=7905,
)
......@@ -3003,8 +3007,8 @@ _DROPOUTPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=7897,
serialized_end=7970,
serialized_start=7907,
serialized_end=7980,
)
......@@ -3068,8 +3072,8 @@ _DUMMYDATAPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=7973,
serialized_end=8133,
serialized_start=7983,
serialized_end=8143,
)
......@@ -3113,8 +3117,8 @@ _ELTWISEPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=8136,
serialized_end=8301,
serialized_start=8146,
serialized_end=8311,
)
......@@ -3143,8 +3147,8 @@ _ELUPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=8303,
serialized_end=8335,
serialized_start=8313,
serialized_end=8345,
)
......@@ -3201,8 +3205,8 @@ _EMBEDPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=8338,
serialized_end=8510,
serialized_start=8348,
serialized_end=8520,
)
......@@ -3245,8 +3249,8 @@ _EXPPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=8512,
serialized_end=8580,
serialized_start=8522,
serialized_end=8590,
)
......@@ -3282,8 +3286,8 @@ _FLATTENPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=8582,
serialized_end=8639,
serialized_start=8592,
serialized_end=8649,
)
......@@ -3326,8 +3330,8 @@ _HDF5DATAPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=8641,
serialized_end=8720,
serialized_start=8651,
serialized_end=8730,
)
......@@ -3356,8 +3360,8 @@ _HDF5OUTPUTPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=8722,
serialized_end=8762,
serialized_start=8732,
serialized_end=8772,
)
......@@ -3387,8 +3391,8 @@ _HINGELOSSPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=8764,
serialized_end=8858,
serialized_start=8774,
serialized_end=8868,
)
......@@ -3494,8 +3498,8 @@ _IMAGEDATAPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=8861,
serialized_end=9140,
serialized_start=8871,
serialized_end=9150,
)
......@@ -3524,8 +3528,8 @@ _INFOGAINLOSSPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=9142,
serialized_end=9181,
serialized_start=9152,
serialized_end=9191,
)
......@@ -3589,8 +3593,8 @@ _INNERPRODUCTPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=9184,
serialized_end=9387,
serialized_start=9194,
serialized_end=9397,
)
......@@ -3619,8 +3623,8 @@ _INPUTPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=9389,
serialized_end=9438,
serialized_start=9399,
serialized_end=9448,
)
......@@ -3663,8 +3667,8 @@ _LOGPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=9440,
serialized_end=9508,
serialized_start=9450,
serialized_end=9518,
)
......@@ -3730,8 +3734,8 @@ _LRNPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=9511,
serialized_end=9823,
serialized_start=9521,
serialized_end=9833,
)
......@@ -3789,8 +3793,8 @@ _MEMORYDATAPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=9826,
serialized_end=10015,
serialized_start=9836,
serialized_end=10025,
)
......@@ -3833,8 +3837,8 @@ _MVNPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=10017,
serialized_end=10118,
serialized_start=10027,
serialized_end=10128,
)
......@@ -3863,8 +3867,8 @@ _PARAMETERPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=10120,
serialized_end=10173,
serialized_start=10130,
serialized_end=10183,
)
......@@ -3972,8 +3976,8 @@ _POOLINGPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=10176,
serialized_end=10594,
serialized_start=10186,
serialized_end=10604,
)
......@@ -4016,8 +4020,8 @@ _ROIPOOLINGPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=10596,
serialized_end=10685,
serialized_start=10606,
serialized_end=10695,
)
......@@ -4060,8 +4064,8 @@ _POWERPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=10687,
serialized_end=10757,
serialized_start=10697,
serialized_end=10767,
)
......@@ -4111,8 +4115,8 @@ _PYTHONPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=10759,
serialized_end=10862,
serialized_start=10769,
serialized_end=10872,
)
......@@ -4156,8 +4160,8 @@ _REDUCTIONPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=10865,
serialized_end=11038,
serialized_start=10875,
serialized_end=11048,
)
......@@ -4194,8 +4198,8 @@ _RELUPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=11041,
serialized_end=11182,
serialized_start=11051,
serialized_end=11192,
)
......@@ -4238,8 +4242,8 @@ _RESHAPEPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=11184,
serialized_end=11274,
serialized_start=11194,
serialized_end=11284,
)
......@@ -4296,8 +4300,8 @@ _SCALEPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=11277,
serialized_end=11442,
serialized_start=11287,
serialized_end=11452,
)
......@@ -4327,8 +4331,8 @@ _SIGMOIDPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=11444,
serialized_end=11564,
serialized_start=11454,
serialized_end=11574,
)
......@@ -4371,8 +4375,8 @@ _SLICEPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=11566,
serialized_end=11642,
serialized_start=11576,
serialized_end=11652,
)
......@@ -4409,8 +4413,8 @@ _SOFTMAXPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=11645,
serialized_end=11782,
serialized_start=11655,
serialized_end=11792,
)
......@@ -4440,8 +4444,8 @@ _TANHPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=11784,
serialized_end=11898,
serialized_start=11794,
serialized_end=11908,
)
......@@ -4484,8 +4488,8 @@ _TILEPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=11900,
serialized_end=11984,
serialized_start=11910,
serialized_end=11994,
)
......@@ -4514,8 +4518,8 @@ _THRESHOLDPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=11986,
serialized_end=12028,
serialized_start=11996,
serialized_end=12038,
)
......@@ -4628,8 +4632,8 @@ _WINDOWDATAPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=12031,
serialized_end=12352,
serialized_start=12041,
serialized_end=12362,
)
......@@ -4674,8 +4678,8 @@ _SPPPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=12355,
serialized_end=12590,
serialized_start=12365,
serialized_end=12600,
)
......@@ -5000,8 +5004,8 @@ _V1LAYERPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=12593,
serialized_end=15121,
serialized_start=12603,
serialized_end=15131,
)
......@@ -5290,8 +5294,8 @@ _V0LAYERPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=15124,
serialized_end=16145,
serialized_start=15134,
serialized_end=16155,
)
......@@ -5327,8 +5331,8 @@ _PRELUPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=16147,
serialized_end=16234,
serialized_start=16157,
serialized_end=16244,
)
......@@ -5357,8 +5361,8 @@ _SMOOTHL1LOSSPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=16236,
serialized_end=16277,
serialized_start=16246,
serialized_end=16287,
)
......@@ -5401,8 +5405,8 @@ _MPIPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=16279,
serialized_end=16351,
serialized_start=16289,
serialized_end=16361,
)
......@@ -5431,8 +5435,8 @@ _PERMUTEPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=16353,
serialized_end=16386,
serialized_start=16363,
serialized_end=16396,
)
......@@ -5482,8 +5486,8 @@ _NORMALIZEPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=16389,
serialized_end=16536,
serialized_start=16399,
serialized_end=16546,
)
......@@ -5526,8 +5530,8 @@ _PARALLELPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=16538,
serialized_end=16633,
serialized_start=16548,
serialized_end=16643,
)
......@@ -5570,8 +5574,8 @@ _RESIZEPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=16635,
serialized_end=16717,
serialized_start=16645,
serialized_end=16727,
)
......@@ -5679,8 +5683,8 @@ _PROPOSALPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=16761,
serialized_end=16961,
serialized_start=16771,
serialized_end=16971,
)
......@@ -5744,8 +5748,8 @@ _BATCHRENORMPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=16964,
serialized_end=17130,
serialized_start=16974,
serialized_end=17140,
)
......@@ -5781,8 +5785,8 @@ _DENSECONCATPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=17132,
serialized_end=17195,
serialized_start=17142,
serialized_end=17205,
)
......@@ -5832,8 +5836,8 @@ _FOCALLOSSPARAMETER = _descriptor.Descriptor(
extension_ranges=[],
oneofs=[
],
serialized_start=17197,
serialized_end=17296,
serialized_start=17207,
serialized_end=17306,
)
_BLOBPROTO.fields_by_name['shape'].message_type = _BLOBSHAPE
......
Dragon/python/dragon/vm/caffe/solver.py
......@@ -296,7 +296,10 @@ class Solver(object):
for i in xrange(self._param.iter_size):
self.train(return_outputs=False)
if root_solver():
for cost in self._net._costs: loss += ws.FetchTensor(cost)[0]
for cost in self._net._costs:
cost_value = ws.FetchTensor(cost)
if cost_value.size == 1:
loss += cost_value[0]
if root_solver():
loss /= self._param.iter_size
......
Dragon/python/dragon/vm/theano/compile/function.py
......@@ -279,6 +279,7 @@ def function(inputs=None, outputs=None, givens=None, updater=None):
external_input_exprs = OrderedDict(external_input_exprs, **new_tensor.expressions)
else:
external_input_exprs = dict(external_input_exprs, **new_tensor.expressions)
external_input_exprs = OrderedDict(sorted(external_input_exprs.items(), lambda x, y: cmp(x[1], y[1])))
elif isinstance(new_tensor, np.ndarray):
ws.FeedTensor(new_tensor, GetTensorName())
external_input_ops = [v for k, v in external_input_exprs.items()]
......
Dragon/src/operators/ndarray/concat_op.cc
......@@ -104,17 +104,6 @@ void ConcatGradientOp<Context>::RunOnDevice() {
else LOG(FATAL) << "Unsupported input types.";
}
template <class Context>
void ConcatGradientOp<Context>::ShareGradient() {
for (int i = 0; i < OutputSize(); i++) {
if (output(i)->name() != "ignore") {
Tensor* dX = ws()->GetBuffer("Grad");
ws()->CreateAvatar(output(i), dX);
break;
}
}
}
DEPLOY_CPU(ConcatGradient);
#ifdef WITH_CUDA
DEPLOY_CUDA(ConcatGradient);
......
Dragon/src/operators/vision/roi_align_op.cc
......@@ -11,17 +11,20 @@ void ROIAlignOp<Context>::RunWithType() {
pool_h, pool_w,
&input(0),
&input(1),
mask,
mask_h,
mask_w,
output(0));
}
template <class Context>
void ROIAlignOp<Context>::RunOnDevice() {
mask = ws()->CreateTensor("/mnt/" + anchor() + "/roi_align_mask");
mask_h = ws()->CreateTensor("/mnt/" + anchor() + "/roi_align_mask_h");
mask_w = ws()->CreateTensor("/mnt/" + anchor() + "/roi_align_mask_w");
vector<TIndex> dims({input(1).dim(0), input(0).dim(1), pool_h, pool_w});
output(0)->Reshape(dims);
mask->Reshape(dims);
mask_h->Reshape(dims);
mask_w->Reshape(dims);
if (input(0).template IsType<float>()) return RunWithType<float>();
else LOG(FATAL) << "Unsupported input types.";
......@@ -39,13 +42,15 @@ void ROIAlignGradientOp<Context>::RunWithType() {
pool_h, pool_w,
&input(-1),
&input(1),
mask,
mask_h,
mask_w,
output(0));
}
template <class Context>
void ROIAlignGradientOp<Context>::RunOnDevice() {
mask = ws()->GetTensor("/mnt/" + anchor() + "/roi_align_mask");
mask_h = ws()->GetTensor("/mnt/" + anchor() + "/roi_align_mask_h");
mask_w = ws()->GetTensor("/mnt/" + anchor() + "/roi_align_mask_w");
output(0)->ReshapeLike(input(0));
......
Dragon/src/utils/op_kernel.cc
......@@ -2640,7 +2640,8 @@ template<> void ROIAlign<float, CPUContext>(const float spatial_scale,
const int pool_h, const int pool_w,
Tensor* x,
Tensor* roi,
Tensor* mask,
Tensor* mask_h,
Tensor* mask_w,
Tensor* y) {
NOT_IMPLEMENTED;
}
......@@ -2649,7 +2650,8 @@ template<> void ROIAlignGrad<float, CPUContext>(const float spatial_scale,
const int pool_h, const int pool_w,
Tensor* dy,
Tensor* roi,
Tensor* mask,
Tensor* mask_h,
Tensor* mask_w,
Tensor* dx) {
NOT_IMPLEMENTED;
}
......
Dragon/src/utils/op_kernel.cu
......@@ -3937,7 +3937,8 @@ __global__ void _ROIAlign(const int count,
const int pool_h, const int pool_w,
const T* x,
const T* roi,
T* mask,
T* mask_h,
T* mask_w,
T* y) {
CUDA_KERNEL_LOOP(idx, count) {
int pw = idx % pool_w;
......@@ -3970,18 +3971,17 @@ __global__ void _ROIAlign(const int count,
bool is_empty = (hend <= hstart) || (wend <= wstart);
T maxval = is_empty ? 0 : -FLT_MAX;
int maxidx = -1;
int x_idx = 0;
T max_h_idx = -1;
T max_w_idx = -1;
x += (roi_batch_ind * channels + c) * height * width;
T h_stride = (hend - hstart) / 3.0;
T w_stride = (wend - wstart) / 3.0;
for (T h = hstart + h_stride; h <= hend - h_stride + 0.01; h += max(h_stride, 0.01)) {
for (T w = wstart + w_stride; w <= wend - w_stride + 0.01; w += max(w_stride, 0.01)) {
x_idx++;
int hlow = min(max(static_cast<int>(floor(h)), 0), height - 1);
int hhigh = min(hlow + 1, height - 1);
int hhigh = min(max(static_cast<int>(ceil(h)), 0), height - 1);
int wleft = min(max(static_cast<int>(floor(w)), 0), width - 1);
int wright = min(wleft + 1, width - 1);
int wright = min(max(static_cast<int>(ceil(w)), 0), width - 1);
int topleft = hlow * width + wleft;
int topright = hlow * width + wright;
int bottomleft = hhigh * width + wleft;
......@@ -3994,12 +3994,14 @@ __global__ void _ROIAlign(const int count,
if (value > maxval) {
maxval = value;
maxidx = x_idx;
max_h_idx = h;
max_w_idx = w;
}
}
}
y[idx] = maxval;
mask[idx] = maxidx;
mask_h[idx] = max_h_idx;
mask_w[idx] = max_w_idx;
}
}
......@@ -4007,12 +4009,14 @@ template<> void ROIAlign<float, CUDAContext>(const float spatial_scale,
const int pool_h, const int pool_w,
Tensor* x,
Tensor* roi,
Tensor* mask,
Tensor* mask_h,
Tensor* mask_w,
Tensor* y) {
auto* Xdata = x->data<float, CUDAContext>();
auto* Rdata = roi->data<float, CUDAContext>();
auto* Ydata = y->mutable_data<float, CUDAContext>();
auto* Mdata = mask->mutable_data<float, CUDAContext>();
auto* MHdata = mask_h->mutable_data<float, CUDAContext>();
auto* MWdata = mask_w->mutable_data<float, CUDAContext>();
TIndex channels = x->dim(1), count = y->count();
TIndex height = x->dim(2), width = x->dim(3);
_ROIAlign<float> << <GET_BLOCKS(count), CUDA_NUM_THREADS >> >(count,
......@@ -4022,7 +4026,8 @@ template<> void ROIAlign<float, CUDAContext>(const float spatial_scale,
pool_h, pool_w,
Xdata,
Rdata,
Mdata,
MHdata,
MWdata,
Ydata);
CUDA_POST_KERNEL_CHECK;
}
......@@ -4036,7 +4041,8 @@ __global__ void _ROIAlignGrad(const int count,
const int pool_h, const int pool_w,
const T* dy,
const T* roi,
const T* mask,
const T* mask_h,
const T* mask_w,
T* dx) {
CUDA_KERNEL_LOOP(idx, count) {
int w = idx % width;
......@@ -4063,53 +4069,28 @@ __global__ void _ROIAlignGrad(const int count,
int offset = (roi_n * channels + c) * pool_h * pool_w;
const T* offset_dy = dy + offset;
const T* offset_mask = mask + offset;
const T* offset_mask_h = mask_h + offset;
const T* offset_mask_w = mask_w + offset;
T roi_width = max(roi_end_w - roi_start_w, static_cast<T>(1));
T roi_height = max(roi_end_h - roi_start_h, static_cast<T>(1));
T bin_size_h = static_cast<T>(roi_height) / static_cast<T>(pool_h);
T bin_size_w = static_cast<T>(roi_width) / static_cast<T>(pool_w);
for (int ph = 0; ph < pool_h; ++ph) {
for (int pw = 0; pw < pool_w; ++pw) {
T hstart = static_cast<T>((ph)* bin_size_h);
T wstart = static_cast<T>((pw)* bin_size_w);
T hend = static_cast<T>((ph + 1) * bin_size_h);
T wend = static_cast<T>((pw + 1) * bin_size_w);
hstart = min(max(hstart + roi_start_h, static_cast<T>(0)), static_cast<T>(height));
hend = min(max(hend + roi_start_h, static_cast<T>(0)), static_cast<T>(height));
wstart = min(max(wstart + roi_start_w, static_cast<T>(0)), static_cast<T>(width));
wend = min(max(wend + roi_start_w, static_cast<T>(0)), static_cast<T>(width));
bool in_bin = (w > wstart - 1.0 &&
w < wend + 1.0 &&
h > hstart - 1.0
&& h < hend + 1.0);
if (!in_bin) continue;
const int pool_idx = ph * pool_w + pw;
int x_idx = 0;
T h_stride = (hend - hstart) / 3.0;
T w_stride = (wend - wstart) / 3.0;
for (T rh = hstart + h_stride; rh <= hend - h_stride + 0.01; rh += max(h_stride, 0.01)) {
for (T rw = wstart + w_stride; rw <= wend - w_stride + 0.01; rw += max(w_stride, 0.01)) {
x_idx++;
if (offset_mask[pool_idx] != x_idx) continue;
int hlow = min(max(static_cast<int>(floor(rh)), 0), height - 1);
int hhigh = min(hlow + 1, height - 1);
int wleft = min(max(static_cast<int>(floor(rw)), 0), width - 1);
int wright = min(wleft + 1, width - 1);
if (h != hlow && h != hhigh && w != wleft && w != wright) continue;
T alpha = (hlow == hhigh) ? static_cast<T>(0.5) : (rh - hlow) / (hhigh - hlow);
T beta = (wleft == wright) ? static_cast<T>(0.5) : (rw - wleft) / (wright - wleft);
if (h == hlow && w == wleft) gradient += offset_dy[pool_idx] * (1 - alpha) * (1 - beta);
else if (h == hlow && w == wright) gradient += offset_dy[pool_idx] * (1 - alpha) * beta;
else if (h == hhigh && w == wleft) gradient += offset_dy[pool_idx] * alpha * (1 - beta);
else if (h == hhigh && w == wright) gradient += offset_dy[pool_idx] * alpha * beta;
}
}
T a_h = offset_mask_h[pool_idx];
T a_w = offset_mask_w[pool_idx];
int hlow = min(max(static_cast<int>(floor(a_h)), 0), height - 1);
int hhigh = min(max(static_cast<int>(ceil(a_h)), 0), height - 1);
int wleft = min(max(static_cast<int>(floor(a_w)), 0), width - 1);
int wright = min(max(static_cast<int>(ceil(a_w)), 0), width - 1);
if (h != hlow && h != hhigh && w != wleft && w != wright) continue;
T alpha = (hlow == hhigh) ? static_cast<T>(0.5) : (a_h - hlow) / (hhigh - hlow);
T beta = (wleft == wright) ? static_cast<T>(0.5) : (a_w - wleft) / (wright - wleft);
if (h == hlow && w == wleft) gradient += offset_dy[pool_idx] * (1 - alpha) * (1 - beta);
else if (h == hlow && w == wright) gradient += offset_dy[pool_idx] * (1 - alpha) * beta;
else if (h == hhigh && w == wleft) gradient += offset_dy[pool_idx] * alpha * (1 - beta);
else if (h == hhigh && w == wright) gradient += offset_dy[pool_idx] * alpha * beta;
}
}
}
......@@ -4121,11 +4102,13 @@ template<> void ROIAlignGrad<float, CUDAContext>(const float spatial_scale,
const int pool_h, const int pool_w,
Tensor* dy,
Tensor* roi,
Tensor* mask,
Tensor* mask_h,
Tensor* mask_w,
Tensor* dx) {
auto* dYdata = dy->data<float, CUDAContext>();
auto* Rdata = roi->data<float, CUDAContext>();
auto* Mdata = mask->data<float, CUDAContext>();
auto* MHdata = mask_h->data<float, CUDAContext>();
auto* MWdata = mask_w->data<float, CUDAContext>();
auto* dXdata = dx->mutable_data<float, CUDAContext>();
TIndex channels = dx->dim(1), count = dx->count();
TIndex height = dx->dim(2), width = dx->dim(3);
......@@ -4137,7 +4120,8 @@ template<> void ROIAlignGrad<float, CUDAContext>(const float spatial_scale,
pool_h, pool_w,
dYdata,
Rdata,
Mdata,
MHdata,
MWdata,
dXdata);
CUDA_POST_KERNEL_CHECK;
}
......
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