It does not want to update: C:\Users\Michael\>pip install --no-deps git+ https://github.com/Theano/Theano.git#egg=Theano Requirement already satisfied: Theano from git+ https://github.com/Theano/Theano.git#egg=Theano in c:\programdata\miniconda2\lib\site-packages
On Tue, Apr 11, 2017 at 2:12 PM, Frédéric Bastien < frederic.bast...@gmail.com> wrote: > http://deeplearning.net/software/theano/install_ubuntu.html#bleeding-edge- > installation-recommended > > > pip install --user --no-deps > git+https://github.com/Theano/Theano.git#egg=Theano > > > > On Tue, Apr 11, 2017 at 12:22 PM Michael Klachko <michaelklac...@gmail.com> > wrote: > >> Thanks! Currently I use the release version of Theano 0.9, installed with >> conda. What's the best way to switch to dev version? Should I just >> overwrite the >> C:\ProgramData\Miniconda2\pkgs\theano-0.9.0-py27_0\Lib\site-packages\theano >> folder? >> >> On Tue, Apr 11, 2017 at 8:02 AM, Frédéric Bastien < >> frederic.bast...@gmail.com> wrote: >> >> Just an updated, we fixed many such useless warning. Update Theano to the >> dev version. If you still see them, tell us. >> >> Fred >> >> On Sat, Mar 25, 2017 at 4:22 AM Michael Klachko <michaelklac...@gmail.com> >> wrote: >> >> Oh, looks like my message got truncated. Here's the complete graph: >> >> >> C:\ProgramData\Miniconda2\lib\site-packages\theano\gof\type.py:405: >> UserWarning: You are creating a TensorVariable with float64 dtype. You >> requested an action via the Theano flag warn_float64={ignore,warn,raise,pdb}. >> >> >> return utils.add_tag_trace(self.make_variable(name)) >> >> C:\ProgramData\Miniconda2\lib\site-packages\theano\gof\graph.py:447: >> UserWarning: You are creating a TensorVariable with float64 dtype. You >> requested an action via the Theano flag warn_float64={ignore,warn, >> raise,pdb}. >> >> cp = self.__class__(self.type, None, None, self.name) >> >> HostFromGpu(gpuarray) [id A] <TensorType(float32, scalar)> 'mean' 84 >> >> |GpuElemwise{Composite{(i0 / Cast{float32}((Composite{Switch(LT(i0, i1), >> i2, i0)}(Composite{Switch(GE(i0, i1), i2, i0)}(Composite{Switch(LT(i0, i1), >> i2, i0)}(Composite{Switch(LT(i0, i1), (i2 + i3), i4)}(i1, i2, i3, i4, i5), >> i6, i7), i8, i9), i10, i11) - Switch(LT(Composite{Switch(LT(i0, i1), i2, >> i0)}(Composite{Switch(GE(i0, i1), i2, i0)}(Composite{Switch(LT(i0, i1), i2, >> i0)}(Composite{Switch(LT(i0, i1), (i2 + i3), i4)}(i12, i13, i14, i15, i16), >> i17, i18), i19, i20), i21, i22), Composite{Switch(LT(i0, i1), i2, >> i0)}(Composite{Switch(GE(i0, i1), i2, i0)}(Composite{Switch(LT(i0, i1), i2, >> i0)}(Composite{Switch(LT(i0, i1), (i2 + i3), i4)}(i1, i2, i3, i4, i5), i6, >> i7), i8, i9), i10, i11)), Composite{Switch(LT(i0, i1), i2, >> i0)}(Composite{Switch(GE(i0, i1), i2, i0)}(Composite{Switch(LT(i0, i1), i2, >> i0)}(Composite{Switch(LT(i0, i1), (i2 + i3), i4)}(i12, i13, i14, i15, i16), >> i17, i18), i19, i20), i21, i22), Composite{Switch(LT(i0, i1), i2, >> i0)}(Composite{Switch(GE(i0, i1), i2, i0)}(Composite{Switch(LT(i0, i1), i2, >> i0)}(Composite{Switch(LT(i0, i1), (i2 + i3), i4)}(i1, i2, i3, i4, i5), i6, >> i7), i8, i9), i10, i11)))))}}[(0, 0)]<gpuarray> [id B] >> <GpuArrayType<None>(float32, ())> '' 83 >> >> |GpuCAReduceCuda{add} [id C] <GpuArrayType<None>(float32, ())> '' 82 >> >> | |GpuElemwise{Composite{EQ(Cast{int32}(i0), i1)}}[]<gpuarray> [id D] >> <GpuArrayType<None>(bool, (False,))> '' 81 >> >> | |GpuSubtensor{int64:int64:} [id E] <GpuArrayType<None>(float32, >> (False,))> '' 27 >> >> | | |<GpuArrayType<None>(float32, (False,))> [id F] >> <GpuArrayType<None>(float32, (False,))> >> >> | | |ScalarFromTensor [id G] <int64> '' 13 >> >> | | | |Elemwise{mul,no_inplace} [id H] <TensorType(int64, scalar)> '' 1 >> >> | | | |TensorConstant{128} [id I] <TensorType(int64, scalar)> >> >> | | | |<TensorType(int64, scalar)> [id J] <TensorType(int64, scalar)> >> >> | | |ScalarFromTensor [id K] <int64> '' 15 >> >> | | |Elemwise{Composite{(i0 * (i1 + i2))}} [id L] <TensorType(int64, >> scalar)> '' 2 >> >> | | |TensorConstant{128} [id I] <TensorType(int64, scalar)> >> >> | | |TensorConstant{1} [id M] <TensorType(int64, scalar)> >> >> | | |<TensorType(int64, scalar)> [id J] <TensorType(int64, scalar)> >> >> | |GpuFromHost<None> [id N] <GpuArrayType<None>(int64, (False,))> '' 80 >> >> | |Argmax [id O] <TensorType(int64, vector)> 'argmax' 79 >> >> | |HostFromGpu(gpuarray) [id P] <TensorType(float32, matrix)> '' 78 >> >> | | |GpuElemwise{Add}[(0, 0)]<gpuarray> [id Q] >> <GpuArrayType<None>(float32, (False, False))> '' 77 >> >> | | |GpuGemm{inplace=True} [id R] <GpuArrayType<None>(float32, (False, >> False))> '' 76 >> >> | | | |GpuAllocEmpty{dtype='float32', context_name=None} [id S] >> <GpuArrayType<None>(float32, (False, False))> '' 75 >> >> | | | | |Subtensor{int64} [id T] <TensorType(int64, scalar)> '' 74 >> >> | | | | | |Shape [id U] <TensorType(int64, vector)> '' 73 >> >> | | | | | | |GpuReshape{2} [id V] <GpuArrayType<None>(float32, (False, >> False))> '' 72 >> >> | | | | | | |GpuElemwise{Composite{(i0 * ((i1 * (i2 + i3)) + (i4 * >> Abs((i2 + i3)))))}}[(0, 2)]<gpuarray> [id W] <GpuArrayType<None>(float32, >> (False, False))> '' 71 >> >> | | | | | | | |GpuArrayConstant{[[ 0.5]]} [id X] >> <GpuArrayType<None>(float32, (True, True))> >> >> | | | | | | | |GpuArrayConstant{[[ 0.1]]} [id Y] >> <GpuArrayType<None>(float32, (True, True))> >> >> | | | | | | | |GpuGemm{inplace=True} [id Z] <GpuArrayType<None>(float32, >> (False, False))> '' 70 >> >> | | | | | | | | |GpuAllocEmpty{dtype='float32', context_name=None} [id >> BA] <GpuArrayType<None>(float32, (False, False))> '' 69 >> >> | | | | | | | | | |Subtensor{int64} [id BB] <TensorType(int64, scalar)> >> '' 68 >> >> | | | | | | | | | | |Shape [id BC] <TensorType(int64, vector)> '' 67 >> >> | | | | | | | | | | | |GpuReshape{2} [id BD] <GpuArrayType<None>(float32, >> (False, False))> '' 66 >> >> | | | | | | | | | | | |GpuElemwise{Composite{(i0 * ((i1 * (i2 + i3)) + >> (i4 * Abs((i2 + i3)))))}}[(0, 2)]<gpuarray> [id BE] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 65 >> >> | | | | | | | | | | | | |GpuArrayConstant{[[[[ 0.5]]]]} [id BF] >> <GpuArrayType<None>(float32, (True, True, True, True))> >> >> | | | | | | | | | | | | |GpuArrayConstant{[[[[ 0.095]]]]} [id BG] >> <GpuArrayType<None>(float32, (True, True, True, True))> >> >> | | | | | | | | | | | | |GpuDnnConv{algo='time_on_shape_change', >> inplace=True} [id BH] <GpuArrayType<None>(float32, (False, False, False, >> False))> '' 64 >> >> | | | | | | | | | | | | | |GpuContiguous [id BI] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 51 >> >> | | | | | | | | | | | | | | |GpuReshape{4} [id BJ] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 50 >> >> | | | | | | | | | | | | | | |GpuElemwise{Composite{(i0 * ((i1 * (i2 + >> i3)) + (i4 * Abs((i2 + i3)))))}}[(0, 2)]<gpuarray> [id BK] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 49 >> >> | | | | | | | | | | | | | | | |GpuArrayConstant{[[[[ 0.5]]]]} [id BF] >> <GpuArrayType<None>(float32, (True, True, True, True))> >> >> | | | | | | | | | | | | | | | |GpuArrayConstant{[[[[ 0.1]]]]} [id BL] >> <GpuArrayType<None>(float32, (True, True, True, True))> >> >> | | | | | | | | | | | | | | | |GpuDnnConv{algo='time_on_shape_change', >> inplace=True} [id BM] <GpuArrayType<None>(float32, (False, False, False, >> False))> '' 48 >> >> | | | | | | | | | | | | | | | | |GpuContiguous [id BN] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 35 >> >> | | | | | | | | | | | | | | | | | |GpuReshape{4} [id BO] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 32 >> >> | | | | | | | | | | | | | | | | | |GpuSubtensor{int64:int64:} [id BP] >> <GpuArrayType<None>(float32, (False, False))> '' 26 >> >> | | | | | | | | | | | | | | | | | | |<GpuArrayType<None>(float32, (False, >> False))> [id BQ] <GpuArrayType<None>(float32, (False, False))> >> >> | | | | | | | | | | | | | | | | | | |ScalarFromTensor [id G] <int64> '' 13 >> >> | | | | | | | | | | | | | | | | | | |ScalarFromTensor [id K] <int64> '' 15 >> >> | | | | | | | | | | | | | | | | | |TensorConstant{[128 3 32 32]} [id BR] >> <TensorType(int32, vector)> >> >> | | | | | | | | | | | | | | | | |GpuContiguous [id BS] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 10 >> >> | | | | | | | | | | | | | | | | | |<GpuArrayType<None>(float32, (False, >> False, False, False))> [id BT] <GpuArrayType<None>(float32, (False, False, >> False, False))> >> >> | | | | | | | | | | | | | | | | |GpuAllocEmpty{dtype='float32', >> context_name=None} [id BU] <GpuArrayType<None>(float32, (False, False, >> False, False))> '' 47 >> >> | | | | | | | | | | | | | | | | | |Assert{msg='The convolution would >> produce an invalid shape (dim[0] < 0).'} [id BV] <TensorType(int64, >> scalar)> '' 44 >> >> | | | | | | | | | | | | | | | | | | |Shape_i{0} [id BW] >> <TensorType(int64, scalar)> '' 38 >> >> | | | | | | | | | | | | | | | | | | | |GpuContiguous [id BN] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 35 >> >> | | | | | | | | | | | | | | | | | | |Elemwise{ge,no_inplace} [id BX] >> <TensorType(bool, scalar)> '' 41 >> >> | | | | | | | | | | | | | | | | | | |Shape_i{0} [id BW] >> <TensorType(int64, scalar)> '' 38 >> >> | | | | | | | | | | | | | | | | | | |TensorConstant{0} [id BY] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | | | | |Assert{msg='The convolution would >> produce an invalid shape (dim[1] < 0).'} [id BZ] <TensorType(int64, >> scalar)> '' 34 >> >> | | | | | | | | | | | | | | | | | | |Shape_i{0} [id CA] >> <TensorType(int64, scalar)> '' 25 >> >> | | | | | | | | | | | | | | | | | | | |GpuContiguous [id BS] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 10 >> >> | | | | | | | | | | | | | | | | | | |Elemwise{ge,no_inplace} [id CB] >> <TensorType(bool, scalar)> '' 31 >> >> | | | | | | | | | | | | | | | | | | |Shape_i{0} [id CA] >> <TensorType(int64, scalar)> '' 25 >> >> | | | | | | | | | | | | | | | | | | |TensorConstant{0} [id CC] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | | | | |Assert{msg='The convolution would >> produce an invalid shape (dim[2] <= 0).'} [id CD] <TensorType(int64, >> scalar)> '' 46 >> >> | | | | | | | | | | | | | | | | | | |Elemwise{Composite{(((i0 - (((i1 - >> i2) * i3) + i4)) // i5) + i6)}}[(0, 0)] [id CE] <TensorType(int64, scalar)> >> '' 40 >> >> | | | | | | | | | | | | | | | | | | | |Shape_i{2} [id CF] >> <TensorType(int64, scalar)> '' 37 >> >> | | | | | | | | | | | | | | | | | | | | |GpuContiguous [id BN] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 35 >> >> | | | | | | | | | | | | | | | | | | | |Shape_i{2} [id CG] >> <TensorType(int64, scalar)> '' 24 >> >> | | | | | | | | | | | | | | | | | | | | |GpuContiguous [id BS] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 10 >> >> | | | | | | | | | | | | | | | | | | | |TensorConstant{1} [id CH] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | | | | | | |TensorConstant{1} [id CI] >> <TensorType(int32, scalar)> >> >> | | | | | | | | | | | | | | | | | | | |TensorConstant{1} [id CH] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | | | | | | |TensorConstant{2} [id CJ] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | | | | | | |TensorConstant{1} [id CH] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | | | | | |Elemwise{gt,no_inplace} [id CK] >> <TensorType(bool, scalar)> '' 43 >> >> | | | | | | | | | | | | | | | | | | |Elemwise{Composite{(((i0 - (((i1 - >> i2) * i3) + i4)) // i5) + i6)}}[(0, 0)] [id CE] <TensorType(int64, scalar)> >> '' 40 >> >> | | | | | | | | | | | | | | | | | | |TensorConstant{0} [id CL] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | | | | |Assert{msg='The convolution would >> produce an invalid shape (dim[3] <= 0).'} [id CM] <TensorType(int64, >> scalar)> '' 45 >> >> | | | | | | | | | | | | | | | | | |Elemwise{Composite{(((i0 - (((i1 - i2) >> * i3) + i4)) // i5) + i6)}}[(0, 0)] [id CN] <TensorType(int64, scalar)> '' >> 39 >> >> | | | | | | | | | | | | | | | | | | |Shape_i{3} [id CO] >> <TensorType(int64, scalar)> '' 36 >> >> | | | | | | | | | | | | | | | | | | | |GpuContiguous [id BN] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 35 >> >> | | | | | | | | | | | | | | | | | | |Shape_i{3} [id CP] >> <TensorType(int64, scalar)> '' 23 >> >> | | | | | | | | | | | | | | | | | | | |GpuContiguous [id BS] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 10 >> >> | | | | | | | | | | | | | | | | | | |TensorConstant{1} [id CH] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | | | | | |TensorConstant{1} [id CI] >> <TensorType(int32, scalar)> >> >> | | | | | | | | | | | | | | | | | | |TensorConstant{1} [id CH] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | | | | | |TensorConstant{2} [id CJ] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | | | | | |TensorConstant{1} [id CH] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | | | | |Elemwise{gt,no_inplace} [id CQ] >> <TensorType(bool, scalar)> '' 42 >> >> | | | | | | | | | | | | | | | | | |Elemwise{Composite{(((i0 - (((i1 - i2) >> * i3) + i4)) // i5) + i6)}}[(0, 0)] [id CN] <TensorType(int64, scalar)> '' >> 39 >> >> | | | | | | | | | | | | | | | | | |TensorConstant{0} [id CR] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | | | |GpuDnnConvDesc{border_mode='valid', >> subsample=(2, 2), conv_mode='conv', precision='float32'} [id CS] >> <CDataType{cudnnConvolutionDescriptor_t}> >> '' 30 >> >> | | | | | | | | | | | | | | | | | |Shape [id CT] <TensorType(int64, >> vector)> '' 22 >> >> | | | | | | | | | | | | | | | | | |GpuContiguous [id BS] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 10 >> >> | | | | | | | | | | | | | | | | |Constant{1.0} [id CU] <float32> >> >> | | | | | | | | | | | | | | | | |Constant{0.0} [id CV] <float32> >> >> | | | | | | | | | | | | | | | |InplaceGpuDimShuffle{x,0,x,x} [id CW] >> <GpuArrayType<None>(float32, (True, False, True, True))> '' 9 >> >> | | | | | | | | | | | | | | | | |<GpuArrayType<None>(float32, (False,))> >> [id CX] <GpuArrayType<None>(float32, (False,))> >> >> | | | | | | | | | | | | | | | |GpuArrayConstant{[[[[ 0.1]]]]} [id BL] >> <GpuArrayType<None>(float32, (True, True, True, True))> >> >> | | | | | | | | | | | | | | |TensorConstant{[128 64 14 14]} [id CY] >> <TensorType(int32, vector)> >> >> | | | | | | | | | | | | | |GpuContiguous [id CZ] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 8 >> >> | | | | | | | | | | | | | | |<GpuArrayType<None>(float32, (False, False, >> False, False))> [id DA] <GpuArrayType<None>(float32, (False, False, False, >> False))> >> >> | | | | | | | | | | | | | |GpuAllocEmpty{dtype='float32', >> context_name=None} [id DB] <GpuArrayType<None>(float32, (False, False, >> False, False))> '' 63 >> >> | | | | | | | | | | | | | | |Assert{msg='The convolution would produce an >> invalid shape (dim[0] < 0).'} [id DC] <TensorType(int64, scalar)> '' 60 >> >> | | | | | | | | | | | | | | | |Shape_i{0} [id DD] <TensorType(int64, >> scalar)> '' 54 >> >> | | | | | | | | | | | | | | | | |GpuContiguous [id BI] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 51 >> >> | | | | | | | | | | | | | | | |Elemwise{ge,no_inplace} [id DE] >> <TensorType(bool, scalar)> '' 57 >> >> | | | | | | | | | | | | | | | |Shape_i{0} [id DD] <TensorType(int64, >> scalar)> '' 54 >> >> | | | | | | | | | | | | | | | |TensorConstant{0} [id DF] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | |Assert{msg='The convolution would produce an >> invalid shape (dim[1] < 0).'} [id DG] <TensorType(int64, scalar)> '' 33 >> >> | | | | | | | | | | | | | | | |Shape_i{0} [id DH] <TensorType(int64, >> scalar)> '' 21 >> >> | | | | | | | | | | | | | | | | |GpuContiguous [id CZ] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 8 >> >> | | | | | | | | | | | | | | | |Elemwise{ge,no_inplace} [id DI] >> <TensorType(bool, scalar)> '' 29 >> >> | | | | | | | | | | | | | | | |Shape_i{0} [id DH] <TensorType(int64, >> scalar)> '' 21 >> >> | | | | | | | | | | | | | | | |TensorConstant{0} [id DJ] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | |Assert{msg='The convolution would produce an >> invalid shape (dim[2] <= 0).'} [id DK] <TensorType(int64, scalar)> '' 62 >> >> | | | | | | | | | | | | | | | |Elemwise{Composite{(((i0 - (((i1 - i2) * >> i3) + i4)) // i5) + i6)}}[(0, 0)] [id DL] <TensorType(int64, scalar)> '' 56 >> >> | | | | | | | | | | | | | | | | |Shape_i{2} [id DM] <TensorType(int64, >> scalar)> '' 53 >> >> | | | | | | | | | | | | | | | | | |GpuContiguous [id BI] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 51 >> >> | | | | | | | | | | | | | | | | |Shape_i{2} [id DN] <TensorType(int64, >> scalar)> '' 20 >> >> | | | | | | | | | | | | | | | | | |GpuContiguous [id CZ] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 8 >> >> | | | | | | | | | | | | | | | | |TensorConstant{1} [id CH] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | | | |TensorConstant{1} [id CI] >> <TensorType(int32, scalar)> >> >> | | | | | | | | | | | | | | | | |TensorConstant{1} [id CH] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | | | |TensorConstant{2} [id CJ] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | | | |TensorConstant{1} [id CH] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | | |Elemwise{gt,no_inplace} [id DO] >> <TensorType(bool, scalar)> '' 59 >> >> | | | | | | | | | | | | | | | |Elemwise{Composite{(((i0 - (((i1 - i2) * >> i3) + i4)) // i5) + i6)}}[(0, 0)] [id DL] <TensorType(int64, scalar)> '' 56 >> >> | | | | | | | | | | | | | | | |TensorConstant{0} [id DP] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | |Assert{msg='The convolution would produce an >> invalid shape (dim[3] <= 0).'} [id DQ] <TensorType(int64, scalar)> '' 61 >> >> | | | | | | | | | | | | | | |Elemwise{Composite{(((i0 - (((i1 - i2) * i3) >> + i4)) // i5) + i6)}}[(0, 0)] [id DR] <TensorType(int64, scalar)> '' 55 >> >> | | | | | | | | | | | | | | | |Shape_i{3} [id DS] <TensorType(int64, >> scalar)> '' 52 >> >> | | | | | | | | | | | | | | | | |GpuContiguous [id BI] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 51 >> >> | | | | | | | | | | | | | | | |Shape_i{3} [id DT] <TensorType(int64, >> scalar)> '' 19 >> >> | | | | | | | | | | | | | | | | |GpuContiguous [id CZ] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 8 >> >> | | | | | | | | | | | | | | | |TensorConstant{1} [id CH] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | | |TensorConstant{1} [id CI] >> <TensorType(int32, scalar)> >> >> | | | | | | | | | | | | | | | |TensorConstant{1} [id CH] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | | |TensorConstant{2} [id CJ] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | | |TensorConstant{1} [id CH] >> <TensorType(int8, scalar)> >> >> | | | | | | | | | | | | | | |Elemwise{gt,no_inplace} [id DU] >> <TensorType(bool, scalar)> '' 58 >> >> | | | | | | | | | | | | | | |Elemwise{Composite{(((i0 - (((i1 - i2) * i3) >> + i4)) // i5) + i6)}}[(0, 0)] [id DR] <TensorType(int64, scalar)> '' 55 >> >> | | | | | | | | | | | | | | |TensorConstant{0} [id DV] <TensorType(int8, >> scalar)> >> >> | | | | | | | | | | | | | |GpuDnnConvDesc{border_mode='valid', >> subsample=(2, 2), conv_mode='conv', precision='float32'} [id DW] >> <CDataType{cudnnConvolutionDescriptor_t}> >> '' 28 >> >> | | | | | | | | | | | | | | |Shape [id DX] <TensorType(int64, vector)> '' >> 18 >> >> | | | | | | | | | | | | | | |GpuContiguous [id CZ] >> <GpuArrayType<None>(float32, (False, False, False, False))> '' 8 >> >> | | | | | | | | | | | | | |Constant{1.0} [id CU] <float32> >> >> | | | | | | | | | | | | | |Constant{0.0} [id CV] <float32> >> >> | | | | | | | | | | | | |InplaceGpuDimShuffle{x,0,x,x} [id DY] >> <GpuArrayType<None>(float32, (True, False, True, True))> '' 7 >> >> | | | | | | | | | | | | | |<GpuArrayType<None>(float32, (False,))> [id >> DZ] <GpuArrayType<None>(float32, (False,))> >> >> | | | | | | | | | | | | |GpuArrayConstant{[[[[ 0.095]]]]} [id BG] >> <GpuArrayType<None>(float32, (True, True, True, True))> >> >> | | | | | | | | | | | |TensorConstant{[ 128 3200]} [id EA] >> <TensorType(int32, vector)> >> >> | | | | | | | | | | |Constant{0} [id EB] <int64> >> >> | | | | | | | | | |Subtensor{int64} [id EC] <TensorType(int64, scalar)> >> '' 17 >> >> | | | | | | | | | |Shape [id ED] <TensorType(int64, vector)> '' 6 >> >> | | | | | | | | | | |w [id EE] <GpuArrayType<None>(float32, (False, >> False))> >> >> | | | | | | | | | |Constant{1} [id EF] <int64> >> >> | | | | | | | | |TensorConstant{0.25} [id EG] <TensorType(float64, >> scalar)> >> >> | | | | | | | | |GpuReshape{2} [id BD] <GpuArrayType<None>(float32, >> (False, False))> '' 66 >> >> | | | | | | | | |w [id EE] <GpuArrayType<None>(float32, (False, False))> >> >> | | | | | | | | |TensorConstant{0.0} [id EH] <TensorType(float64, scalar)> >> >> | | | | | | | |InplaceGpuDimShuffle{x,0} [id EI] >> <GpuArrayType<None>(float32, (True, False))> '' 5 >> >> | | | | | | | | |b [id EJ] <GpuArrayType<None>(float32, (False,))> >> >> | | | | | | | |GpuArrayConstant{[[ 0.1]]} [id Y] >> <GpuArrayType<None>(float32, (True, True))> >> >> | | | | | | |TensorConstant{[128 390]} [id EK] <TensorType(int32, vector)> >> >> | | | | | |Constant{0} [id EB] <int64> >> >> | | | | |Subtensor{int64} [id EL] <TensorType(int64, scalar)> '' 16 >> >> | | | | |Shape [id EM] <TensorType(int64, vector)> '' 4 >> >> | | | | | |w [id EN] <GpuArrayType<None>(float32, (False, False))> >> >> | | | | |Constant{1} [id EF] <int64> >> >> | | | |TensorConstant{0.25} [id EG] <TensorType(float64, scalar)> >> >> | | | |GpuReshape{2} [id V] <GpuArrayType<None>(float32, (False, False))> >> '' 72 >> >> | | | |w [id EN] <GpuArrayType<None>(float32, (False, False))> >> >> | | | |TensorConstant{0.0} [id EH] <TensorType(float64, scalar)> >> >> | | |InplaceGpuDimShuffle{x,0} [id EO] <GpuArrayType<None>(float32, >> (True, False))> '' 3 >> >> | | |b [id EP] <GpuArrayType<None>(float32, (False,))> >> >> | |TensorConstant{(1L,) of 1} [id EQ] <TensorType(int32, (True,))> >> >> |GpuFromHost<None> [id ER] <GpuArrayType<None>(int64, ())> '' 14 >> >> | |Elemwise{Composite{(i0 * (i1 + i2))}} [id L] <TensorType(int64, >> scalar)> '' 2 >> >> |GpuArrayConstant{0} [id ES] <GpuArrayType<None>(int8, ())> >> >> |GpuFromHost<None> [id ER] <GpuArrayType<None>(int64, ())> '' 14 >> >> |GpuFromHost<None> [id ET] <GpuArrayType<None>(int64, ())> '' 11 >> >> | |Shape_i{0} [id EU] <TensorType(int64, scalar)> '' 0 >> >> | |<GpuArrayType<None>(float32, (False,))> [id F] >> <GpuArrayType<None>(float32, (False,))> >> >> |GpuFromHost<None> [id ER] <GpuArrayType<None>(int64, ())> '' 14 >> >> |GpuArrayConstant{0} [id ES] <GpuArrayType<None>(int8, ())> >> >> |GpuArrayConstant{-1} [id EV] <GpuArrayType<None>(int8, ())> >> >> |GpuFromHost<None> [id ET] <GpuArrayType<None>(int64, ())> '' 11 >> >> |GpuFromHost<None> [id ET] <GpuArrayType<None>(int64, ())> '' 11 >> >> |GpuArrayConstant{0} [id ES] <GpuArrayType<None>(int8, ())> >> >> |GpuArrayConstant{0} [id ES] <GpuArrayType<None>(int8, ())> >> >> |GpuFromHost<None> [id EW] <GpuArrayType<None>(int64, ())> '' 12 >> >> | |Elemwise{mul,no_inplace} [id H] <TensorType(int64, scalar)> '' 1 >> >> |GpuArrayConstant{0} [id ES] <GpuArrayType<None>(int8, ())> >> >> |GpuFromHost<None> [id EW] <GpuArrayType<None>(int64, ())> '' 12 >> >> |GpuFromHost<None> [id ET] <GpuArrayType<None>(int64, ())> '' 11 >> >> |GpuFromHost<None> [id EW] <GpuArrayType<None>(int64, ())> '' 12 >> >> |GpuArrayConstant{0} [id ES] <GpuArrayType<None>(int8, ())> >> >> |GpuArrayConstant{0} [id ES] <GpuArrayType<None>(int8, ())> >> >> |GpuFromHost<None> [id ET] <GpuArrayType<None>(int64, ())> '' 11 >> >> |GpuFromHost<None> [id ET] <GpuArrayType<None>(int64, ())> '' 11 >> >> |GpuArrayConstant{0} [id ES] <GpuArrayType<None>(int8, ())> >> >> |GpuArrayConstant{0} [id ES] <GpuArrayType<None>(int8, ())> >> >> -- >> >> --- >> You received this message because you are subscribed to the Google Groups >> "theano-users" group. >> To unsubscribe from this group and stop receiving emails from it, send an >> email to theano-users+unsubscr...@googlegroups.com. >> For more options, visit https://groups.google.com/d/optout. >> >> -- >> >> --- >> You received this message because you are subscribed to a topic in the >> Google Groups "theano-users" group. 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