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tensorflow/compiler/mlir/quantization/common/uniform_quantized_types.h
// storage type. The available values use the full range of the storage value, // i.e. [-128, 127]. Assumes asymmetric quantization, meaning the zero point // value can be a non-zero value. // If `narrow_range` is set true (ex: for weights), a restricted range of // integers will be used for symmetric mapping, i.e. [-127, 127]. UniformQuantizedType CreateI8F32UniformQuantizedType(Location loc,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 5.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization.td
there's any, and set it to True. The reason behind this decision is that generally activations of these ops show better accuracy with asymmetric input quantization so we want to deprecate symmetric activation quantization for those ops eventually. - Unlike to the old quantizer, per-channel quantization is supported for weight-only TransposeConvOp. }];
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 05 07:39:40 UTC 2024 - 8.3K bytes - Viewed (0) -
platforms/ide/tooling-api/src/crossVersionTest/groovy/org/gradle/integtests/tooling/r85/TestFailureProgressEventCrossVersionTest.groovy
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Fri Nov 10 17:52:51 UTC 2023 - 12.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/schema/schema_v3b.fbs
union QuantizationDetails { CustomQuantization, } // Parameters for converting a quantized tensor back to float. table QuantizationParameters { // These four parameters are the asymmetric linear quantization parameters. // Given a quantized value q, the corresponding float value f should be: // f = scale * (q - zero_point) // For other quantization types, the QuantizationDetails below is used.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 14:28:27 UTC 2024 - 30K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/test_schema.fbs
union QuantizationDetails { CustomQuantization, } // Parameters for converting a quantized tensor back to float. table QuantizationParameters { // These four parameters are the asymmetric linear quantization parameters. // Given a quantized value q, the corresponding float value f should be: // f = scale * (q - zero_point) // For other quantization types, the QuantizationDetails below is used.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 19 19:46:06 UTC 2021 - 26.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/schema/schema.fbs
union QuantizationDetails { CustomQuantization, } // Parameters for converting a quantized tensor back to float. table QuantizationParameters { // These four parameters are the asymmetric linear quantization parameters. // Given a quantized value q, the corresponding float value f should be: // f = scale * (q - zero_point) // For other quantization types, the QuantizationDetails below is used.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 18:01:23 UTC 2024 - 41.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/quantized_function_library_xla_weight_only.mlir
attr_map = "strides:0,use_cudnn_on_gpu:1,padding:2,explicit_paddings:3,dilations:4" } : (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32> func.return %3 : tensor<*xf32> } // TODO(b/269387785): Support asymmetric quantization for weight with weight-only scheme. parameters[ {"quantized_ops": ["MatMul"], "internal_func_name": "internal_matmul_fn"}, {"quantized_ops": ["Conv2D"], "internal_func_name": "internal_conv2d_fn"},
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 03 15:43:38 UTC 2023 - 7K bytes - Viewed (0) -
docs/bucket/replication/DESIGN.md
### Replication of DeleteMarker and versioned Delete
Registered: Sun Jun 16 00:44:34 UTC 2024 - Last Modified: Thu Sep 29 04:28:45 UTC 2022 - 14.7K bytes - Viewed (0) -
src/crypto/crypto.go
// the message passed to Signer.Sign, or else zero to indicate that no // hashing was done. HashFunc() Hash } // Decrypter is an interface for an opaque private key that can be used for // asymmetric decryption operations. An example would be an RSA key // kept in a hardware module. type Decrypter interface { // Public returns the public key corresponding to the opaque, // private key. Public() PublicKey
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Fri Oct 13 17:09:47 UTC 2023 - 6.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_utils.cc
} else if (width == 8) { // This can be a state tensor, or an actual constant tensor with // asymmetric range. For a state tensor, assigning correct quantization // parameters is sufficient, and for constants with asymmetric range it's // not correctly quantized by legacy quantizer so call the new Quantize. return Quantize(real_value, tensor_type); } else if (width == 16) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 02:10:16 UTC 2024 - 43.2K bytes - Viewed (0)