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tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test.py
rng = np.random.default_rng(seed=42) input_data = ops.convert_to_tensor( rng.uniform(low=0.0, high=1.0, size=static_input_shape).astype( np.float32 ) ) def data_gen() -> repr_dataset.RepresentativeDataset: for _ in range(100): yield { 'input_tensor': rng.uniform( low=0.0, high=1.0, size=static_input_shape ).astype(np.float32)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 06:31:57 UTC 2024 - 51.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf.mlir
^bb0(%arg0: tensor<1x2xf32>): %cst_0 = arith.constant dense<[1, 0]> : tensor<2xi32> %0 = "tfl.quantize"(%arg0){qtype = tensor<1x2x!quant.uniform<u8:f32, 1.0>>}: (tensor<1x2xf32>) -> (tensor<1x2x!quant.uniform<u8:f32, 1.0>>) %1 = "tfl.dequantize"(%0): (tensor<1x2x!quant.uniform<u8:f32, 1.0>>) -> (tensor<1x2xf32>) %2 = "tf.Transpose"(%1, %cst_0): (tensor<1x2xf32>, tensor<2xi32>) -> tensor<2x1xf32> func.return %2 : tensor<2x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 07:26:59 UTC 2024 - 59.8K bytes - Viewed (0) -
platforms/documentation/docs/src/docs/userguide/releases/upgrading/upgrading_version_8.adoc
At the same time, this behavior can be confusing for users as they can experience a failing test in a successful build. To make the two APIs more uniform, we made `TestLauncher` also fail the build, which is a potential breaking change. To continue the test execution even if a test task failed, Tooling API clients should explicitly pass `--continue` to the build.
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Fri Jun 07 17:01:07 UTC 2024 - 90.7K bytes - Viewed (0)