Fix typo in convert_image_to_dtype
PiperOrigin-RevId: 169252296
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095f6aa7d1
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@ -1061,7 +1061,7 @@ def convert_image_dtype(image, dtype, saturate=False, name=None):
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# Scaling up, cast first, then scale. The scale will not map in.max to
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# out.max, but converting back and forth should result in no change.
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if saturate:
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cast = math_ops.saturate_cast(scaled, dtype)
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cast = math_ops.saturate_cast(image, dtype)
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else:
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cast = math_ops.cast(image, dtype)
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scale = (scale_out + 1) // (scale_in + 1)
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@ -2655,6 +2655,12 @@ class ConvertImageTest(test_util.TensorFlowTestCase):
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y = image_ops.convert_image_dtype(image, output_dtype)
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self.assertTrue(y.dtype == output_dtype)
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self.assertAllClose(y.eval(), y_np, atol=1e-5)
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if output_dtype in [dtypes.float32, dtypes.float64,
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dtypes.int32, dtypes.int64]:
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y_saturate = image_ops.convert_image_dtype(
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image, output_dtype, saturate=True)
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self.assertTrue(y_saturate.dtype == output_dtype)
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self.assertAllClose(y_saturate.eval(), y_np, atol=1e-5)
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def testNoConvert(self):
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# Make sure converting to the same data type creates only an identity op
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@ -2670,6 +2676,8 @@ class ConvertImageTest(test_util.TensorFlowTestCase):
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with self.test_session(use_gpu=True):
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self._convert([0, 255], dtypes.uint8, dtypes.int16, [0, 255 * 128])
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self._convert([0, 32767], dtypes.int16, dtypes.uint8, [0, 255])
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self._convert([0, 2 ** 32], dtypes.int64, dtypes.int32, [0, 1])
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self._convert([0, 1], dtypes.int32, dtypes.int64, [0, 2 ** 32])
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def testConvertBetweenFloat(self):
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# Make sure converting to between float types does nothing interesting
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