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[Relay] QLinearMatMul allows 1D weight_scale, weight_zero_point inputs #10047

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Merged
masahi merged 5 commits into from
Jan 26, 2022
Merged

[Relay] QLinearMatMul allows 1D weight_scale, weight_zero_point inputs #10047

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e41a717
fix after cr
yuanfz98 Jan 24, 2022
246149f
fix after cr 2
yuanfz98 Jan 25, 2022
dbd14b5
emptycommit
yuanfz98 Jan 25, 2022
03fcb8e
emptycommit 2nd try
yuanfz98 Jan 26, 2022
506865a
Merge branch 'apache:main' into qlinearmatmul_v3
yuanfz98 Jan 26, 2022
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28 changes: 13 additions & 15 deletions python/tvm/relay/frontend/onnx.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3804,18 +3804,16 @@ def _impl_v10(cls, inputs, attr, params):
#
# This function attempts to present 'x' in a form that meets both of those
# requirements.
def try_resolve_to_const_scalar(x, dtype_override=None):
def try_resolve_to_const(x, dtype_override=None):
x2 = try_resolve_var_to_const(x, params)
x3 = ensure_scalar_shape(x2)

num_elem = np.prod(infer_shape(x))
if num_elem == 1:
x2 = ensure_scalar_shape(x2)
x_dtype = infer_type(x).checked_type.dtype
if (dtype_override is not None) and (dtype_override != x_dtype):
x4 = _op.cast(x3, dtype_override)
else:
x4 = x3

x5 = fold_constant(x4)
return x5
x2 = _op.cast(x2, dtype_override)
x3 = fold_constant(x2)
return x3

# Unpack the inputs and obtain some type info...
a, a_scale, a_zp, b, b_scale, b_zp, y_scale, y_zp = inputs
Expand Down Expand Up @@ -3855,14 +3853,14 @@ def try_resolve_to_const_scalar(x, dtype_override=None):
)

# _qnn.op.dense requires the zero-point values to have dtype int32.
a_scale_scalar = try_resolve_to_const_scalar(a_scale)
a_zp_scalar = try_resolve_to_const_scalar(a_zp, "int32")
a_scale_scalar = try_resolve_to_const(a_scale)
a_zp_scalar = try_resolve_to_const(a_zp, "int32")

b_scale_scalar = try_resolve_to_const_scalar(b_scale)
b_zp_scalar = try_resolve_to_const_scalar(b_zp, "int32")
b_scale_scalar = try_resolve_to_const(b_scale)
b_zp_scalar = try_resolve_to_const(b_zp, "int32")

y_scale_scalar = try_resolve_to_const_scalar(y_scale)
y_zp_scalar = try_resolve_to_const_scalar(y_zp, "int32")
y_scale_scalar = try_resolve_to_const(y_scale)
y_zp_scalar = try_resolve_to_const(y_zp, "int32")

# TODO: Confirm that we're using 'num_hidden_units' correctly / as intended with
# the '_qnn.op.dense' instance below.
Expand Down