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[FRONTEND][MXNET] support elemwise logic ops #5361

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Apr 24, 2020
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[FRONTEND][MXNET] support elemwise logic ops #5361

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6 changes: 6 additions & 0 deletions python/tvm/relay/frontend/mxnet.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1737,6 +1737,12 @@ def _get_bias_requantize_scale(_inputs, _data_scale, _kernel_scale):
"broadcast_greater_equal": _mx_compare(_op.greater_equal, _rename),
"broadcast_lesser" : _mx_compare(_op.less, _rename),
"broadcast_lesser_equal" : _mx_compare(_op.less_equal, _rename),
"_equal" : _mx_compare(_op.equal, _rename),
"_not_equal" : _mx_compare(_op.not_equal, _rename),
"_greater" : _mx_compare(_op.greater, _rename),
"_greater_equal" : _mx_compare(_op.greater_equal, _rename),
"_lesser" : _mx_compare(_op.less, _rename),
"_lesser_equal" : _mx_compare(_op.less_equal, _rename),
"elemwise_add" : _rename(_op.add),
"elemwise_sub" : _rename(_op.subtract),
"elemwise_mul" : _rename(_op.multiply),
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12 changes: 9 additions & 3 deletions tests/python/frontend/mxnet/test_forward.py
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Expand Up @@ -328,13 +328,19 @@ def test_forward_broadcast_ops():

def test_forward_elemwise_ops():
for op in ["elemwise_add", "elemwise_sub", "elemwise_mul",
"elemwise_div", "maximum", "minimum"]:
"elemwise_div", "maximum", "minimum",
operator.lt, operator.le, operator.eq,
operator.ne, operator.gt, operator.ge]:
shape = (3, 4, 5)
dtype = 'float32'
a_np = np.random.uniform(size=shape).astype(dtype)
b_np = np.random.uniform(size=shape).astype(dtype)
mx_sym = _mx_symbol(mx.sym, op, [mx.sym.var('a'), mx.sym.var('b')])
ref_res = _mx_symbol(mx.nd, op, [mx.nd.array(a_np), mx.nd.array(b_np)])
if type(op) == str:
mx_sym = _mx_symbol(mx.sym, op, [mx.sym.var('a'), mx.sym.var('b')])
ref_res = _mx_symbol(mx.nd, op, [mx.nd.array(a_np), mx.nd.array(b_np)])
else:
mx_sym = op(mx.sym.var('a'), mx.sym.var('b'))
ref_res = op(mx.nd.array(a_np), mx.nd.array(b_np))
shapes = {'a': shape, 'b': shape}
mod, _ = relay.frontend.from_mxnet(mx_sym, shapes, dtype)
for target, ctx in ctx_list():
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