'elemwise_add': _add,
# Subtraction
'__sub_scalar__': _subtract,
'__rsub_scalar__': _rsubtract,
'broadcast_sub': _subtract,
'elemwise_sub': _subtract,
# Multiply
'__mul_scalar__': _multiply,
'broadcast_mul': _multiply,
'elemwise_mul': _multiply,
# Division
'__div_scalar__': _divide,
'broadcast_div': _divide,
'elemwise_div': _divide,
# Negative
'negative': _rename("negative"),
# Comparsion
'greater': _greater,
'greater_equal': _greater_equal,
'less': _less,
'less_equal': _less_equal,
# Activations
'sigmoid': _rename('sigmoid'),
'relu': _rename('nn.relu'),
'exp': _rename('exp'),
'log': _rename('log'),
'tanh': _rename('tanh'),
'leaky_relu': _leaky_relu,
'clip': _clip,
NNVM_OP_2_RELAY_OP = {
'flatten': _nn_batch_flatten,
'dense': _dense,
'softmax': _softmax_op(op.nn.softmax),
'log_softmax': _softmax_op(op.nn.log_softmax),
'conv2d': _conv2d,
'batch_norm': _batch_norm,
'max_pool2d': _max_pool2d,
'reshape': _reshape,
'transpose': _transpose,
'dropout': _dropout,
'mean': _mean,
# Addition
'__add_scalar__': _binop_scalar(op.add),
'broadcast_add': _rename(op.add),
'elemwise_add': _rename(op.add),
# Subtraction
'__sub_scalar__': _binop_scalar(op.subtract),
'__rsub_scalar__': _rbinop_scalar(op.subtract),
'broadcast_sub': _rename(op.subtract),
'elemwise_sub': _rename(op.subtract),
# Multiply
'__mul_scalar__': _binop_scalar(op.multiply),
'broadcast_mul': _rename(op.multiply),
'elemwise_mul': _rename(op.multiply),
# Division
'__div_scalar__': _binop_scalar(op.divide),
'broadcast_div': _rename(op.divide),
'elemwise_div': _rename(op.divide),
'broadcast_mod': _rename(op.mod),