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[Relay][FQ2I]: Use appropriate dtype while quantizing relay.op.nn.pad… #17177

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Jul 22, 2024
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[Relay][FQ2I]: Use appropriate dtype while quantizing relay.op.nn.pad… #17177

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[Relay][FQ2I]: Use appropriate dtype while quantizing relay.op.nn.pad…
arangasa Jul 19, 2024
54d81c8
Keep default axis
arangasa Jul 20, 2024
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[Relay][FQ2I]: Use appropriate dtype while quantizing relay.op.nn.pad… 
…'s constant pad value
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@arangasa
arangasa committed Jul 19, 2024
commit ee654afa093bffe18f6bdcedf0e27d061278d996
2 changes: 1 addition & 1 deletion python/tvm/relay/transform/fake_quantization_to_integer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -466,7 +466,7 @@ def pad(expr, type_map):
# If the pad-value is a constant, we need to quantize it
assert isinstance(pad_value, relay.expr.Constant)
assert pad_value.checked_type.dtype in ["float32", "float64", "float16", "bfloat16"]
pad_value = relay.qnn.op.quantize(pad_value, t.scale, t.zero_point)
pad_value = relay.qnn.op.quantize(pad_value, t.scale, t.zero_point, t.axis, t.dtype)

out = relay.op.nn.pad(arg, pad_value=pad_value, **expr.attrs)
return [out, t]
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14 changes: 14 additions & 0 deletions tests/python/relay/test_pass_fake_quantization_to_integer.py
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Expand Up @@ -814,6 +814,20 @@ def test_fake_quantize_pad():
compare_fq_to_int(op, [x_np])


def test_fake_quantize_pad_with_float_min():
in_shape = [1, 383, 128]
x = relay.var("x", shape=in_shape, dtype="float32")
op = relay.qnn.quantize(x, relay.const(1.0), relay.const(0), out_dtype="uint8")
op = relay.qnn.dequantize(op, relay.const(1.0), relay.const(0), out_dtype="float32")
op = relay.op.nn.pad(
op, pad_width=[[0, 0], [0, 1], [0, 0]], pad_value=relay.const(-3.40282e38, dtype="float32")
)
op = relay.qnn.op.quantize(op, relay.const(1.0), relay.const(0), out_dtype="uint8")
x_np = np.random.randint(0, 256, size=in_shape)
x_as_float = x_np.astype("float32")
compare_fq_to_int(op, [x_as_float], True)


def test_fake_quantize_depth_to_space():
x = relay.var("x", shape=[1, 3, 224, 224], dtype="int8")

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