Method get_param_to_grad

caffe2/python/model_helper.py:333–347

Given a list of parameters returns a dict from a parameter to a corresponding gradient

(self, params)

        return self.grad_map

    def get_param_to_grad(self, params):
        '''
        Given a list of parameters returns a dict from a parameter
        to a corresponding gradient
        '''

        param_to_grad = {}
        if not self.gradient_ops_added:
            raise RuntimeError("You need to run AddGradientOperators first.")
        # We need to use empty namescope when creating the gradients
        # to prevent duplicating the namescope prefix for gradient blobs.
        for p in params:
            if str(p) in self.grad_map:
                param_to_grad[p] = self.grad_map[str(p)]
        return param_to_grad

    def GetOptimizationParamInfo(self, params=None):
        '''