opt.py 文件源码

def local_abstractconv_gradinputs_gemm(node):
    if theano.config.cxx == "" or not theano.config.blas.ldflags:
        return
    if not isinstance(node.op, AbstractConv2d_gradInputs):
        return None
    kern, topgrad, shape = node.inputs
    if not isinstance(kern.type, TensorType) or \
       not isinstance(topgrad.type, TensorType):
        return None

    # need to flip the kernel if necessary
    if node.op.filter_flip:
        kern = kern[:, :, ::-1, ::-1]
    rval = CorrMM_gradInputs(border_mode=node.op.border_mode,
                             subsample=node.op.subsample,
                             filter_dilation=node.op.filter_dilation)(kern, topgrad,
                                                                      shape)
    copy_stack_trace(node.outputs[0], rval)

    return [rval]