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[Quant tool] Fix quantized bias's scale dtype to properly handle fp16 bias inputs (#20340)

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### Description
- Fix quantization tool bug that did not correctly set a quantized
bias's scale data type to fp16 if the original bias was fp16.
- Enabled fp16 ConvTranspose quantization unit tests that were disabled.



### Motivation and Context
Python quantization tests for fp16 ConvTranspose were originally
disabled due to a shape inference bug. It turns out that we also have a
bug in our quantizer that does not properly handle fp16 bias inputs.
Fixing the bug allows us to re-enable these tests with the latest
version of ONNX.
This commit is contained in:
Adrian Lizarraga 2024-04-17 10:24:28 -07:00 committed by GitHub
parent 0a1902525f
commit eae7b705ac
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2 changed files with 4 additions and 4 deletions
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4
onnxruntime/python/tools/quantization/base_quantizer.py
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@ -235,7 +235,9 @@ class BaseQuantizer:
bias_np_data = np.asarray(quantized_data, dtype=np.int32).reshape(bias_initializer.dims)
packed_bias_initializer = onnx.numpy_helper.from_array(bias_np_data, quantized_bias_name)
self.model.initializer_extend([packed_bias_initializer])
bias_scale_data = np.asarray(bias_scale, dtype=np.float32).reshape(-1)
# Bias's scale dtype should match the original bias data's unquantized type (float32 or float16).
bias_scale_data = np.asarray(bias_scale, dtype=bias_data.dtype).reshape(-1)
node_type = "DequantizeLinear"
node_qtype = self.weight_qType

4
onnxruntime/test/python/quantization/test_op_conv_transpose.py
View file

@ -149,7 +149,6 @@ class TestOpConvTranspose(unittest.TestCase):
def test_quantize_conv_transpose_u8u8(self):
self.quantize_conv_transpose_u8u8(TensorProto.FLOAT, 13, 7)
@unittest.skip(reason="Shape inference bug, see onnx PR #5709")
def test_quantize_conv_transpose_u8u8_fp16(self):
self.quantize_conv_transpose_u8u8(TensorProto.FLOAT16, 19, 9)
@ -160,7 +159,7 @@ class TestOpConvTranspose(unittest.TestCase):
np.random.seed(1)
model_fp32_path = "conv_transpose_fp32.onnx"
self.construct_model(model_fp32_path)
self.construct_model(model_fp32_path, onnx_type, opset, ir_version)
dtype = onnx.helper.tensor_dtype_to_np_dtype(onnx_type)
data_reader = self.input_feeds(1, {"input": [1, 1, 7, 7]}, dtype)
@ -175,7 +174,6 @@ class TestOpConvTranspose(unittest.TestCase):
def test_quantize_conv_transpose_s8s8(self):
self.quantize_conv_transpose_s8s8(TensorProto.FLOAT, 13, 7)
@unittest.skip(reason="Shape inference bug, see onnx PR #5709")
def test_quantize_conv_transpose_s8s8_fp16(self):
self.quantize_conv_transpose_s8s8(TensorProto.FLOAT16, 19, 9)