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https://github.com/Evolution-X/hardware_interfaces
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Update TRANSPOSE_CONV_2D docs
* Add info about per-channel quantization
* Update current.txt
Test: mma
Change-Id: I197d984c8b65b4c46bf526eb137f212ad8844926
Merged-In: I197d984c8b65b4c46bf526eb137f212ad8844926
(cherry picked from commit 44015c090a)
This commit is contained in:
@@ -420,7 +420,7 @@ dd1ec219f5d2e2b33c6c0bcb92e63bbedb36f7c716413462848f6b6ae74fc864 android.hardwar
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92714960d1a53fc2ec557302b41c7cc93d2636d8364a44bd0f85be0c92927ff8 android.hardware.neuralnetworks@1.2::IExecutionCallback
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83885d366f22ada42c00d8854f0b7e7ba4cf73ddf80bb0d8e168ce132cec57ea android.hardware.neuralnetworks@1.2::IPreparedModel
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e1c734d1545e1a4ae749ff1dd9704a8e594c59aea7c8363159dc258e93e0df3b android.hardware.neuralnetworks@1.2::IPreparedModelCallback
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313b341f1f6196a48cf304eaf067f67510c1ebc04df8c7cd536db5611df5c5c2 android.hardware.neuralnetworks@1.2::types
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769f8650631eef7a3ceedc8cf130f4b99eb52fe698a11609d55de32985a3dddf android.hardware.neuralnetworks@1.2::types
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cf7a4ba516a638f9b82a249c91fb603042c2d9ca43fd5aad9cf6c0401ed2a5d7 android.hardware.nfc@1.2::INfc
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abf98c2ae08bf765db54edc8068e36d52eb558cff6706b6fd7c18c65a1f3fc18 android.hardware.nfc@1.2::types
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4cb252dc6372a874aef666b92a6e9529915aa187521a700f0789065c3c702ead android.hardware.power.stats@1.0::IPowerStats
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@@ -342,7 +342,7 @@ enum OperationType : int32_t {
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* * * input.scale * filter.scale).
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*
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* Available since API level 29:
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* * Quantized with symetric per channel quantization for the filter:
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* * Quantized with symmetric per channel quantization for the filter:
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* * * {@link OperandType::TENSOR_QUANT8_ASYMM} for input, and output.
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* * * {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} for filter.
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* * * {@link OperandType::TENSOR_INT32} for bias (scale set to 0.0,
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@@ -491,7 +491,7 @@ enum OperationType : int32_t {
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* * * input.scale * filter.scale).
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*
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* Available since API level 29:
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* * Quantized with symetric per channel quantization for the filter:
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* * Quantized with symmetric per channel quantization for the filter:
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* * * {@link OperandType::TENSOR_QUANT8_ASYMM} for input, and output.
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* * * {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} for filter.
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* * * {@link OperandType::TENSOR_INT32} for bias (scale set to 0.0,
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@@ -3018,7 +3018,7 @@ enum OperationType : int32_t {
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* * * {@link OperandType::TENSOR_INT32} for bias (with scale set to
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* * * input.scale * filter.scale).
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*
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* * Quantized with symetric per channel quantization for the filter:
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* * Quantized with symmetric per channel quantization for the filter:
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* * * {@link OperandType::TENSOR_QUANT8_ASYMM} for input, and output.
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* * * {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} for filter.
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* * * {@link OperandType::TENSOR_INT32} for bias (scale set to 0.0,
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@@ -4204,10 +4204,21 @@ enum OperationType : int32_t {
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* The output dimensions are functions of the filter dimensions, stride, and
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* padding.
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*
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* Supported tensor {@link OperandType}:
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* * {@link OperandType::TENSOR_FLOAT16}
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* * {@link OperandType::TENSOR_FLOAT32}
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* * {@link OperandType::TENSOR_QUANT8_ASYMM}
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* Supported tensor {@link OperandCode} configurations:
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* * 32 bit Floating point :
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* * * {@link OperandType::TENSOR_FLOAT32} for input, filter, output, and bias.
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*
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* * Quantized:
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* * * {@link OperandType::TENSOR_QUANT8_ASYMM} for input, filter, and output.
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* * * {@link OperandType::TENSOR_INT32} for bias (with scale set to
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* * * input.scale * filter.scale).
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*
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* Available since API level 29:
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* * Quantized with symmetric per channel quantization for the filter:
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* * * {@link OperandType::TENSOR_QUANT8_ASYMM} for input, and output.
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* * * {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} for filter.
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* * * {@link OperandType::TENSOR_INT32} for bias (scale set to 0.0,
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* * * each value scaling is separate and equal to input.scale * filter.scales[channel]).
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*
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* Supported tensor rank: 4, with "NHWC" or "NCHW" data layout.
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* With the default data layout NHWC, the data is stored in the order of:
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@@ -4221,14 +4232,20 @@ enum OperationType : int32_t {
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* specifying the input.
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* * 1: A 4-D tensor, of shape
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* [depth_out, filter_height, filter_width, depth_in], specifying the
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* filter.
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* filter. For tensor of type
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* {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} the channel
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* dimension (extraParams.channelQuant.channelDim) must be set to 0.
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* * 2: A 1-D tensor, of shape [depth_out], specifying the bias. For input
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* tensor of type {@link OperandType::TENSOR_FLOAT32} or
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* {@link OperandType::TENSOR_FLOAT16}, the bias should be of the
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* same type. For input tensor of type
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* {@link OperandType::TENSOR_QUANT8_ASYMM}, the bias should be
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* of {@link OperandType::TENSOR_INT32}, with zeroPoint of 0 and
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* bias_scale == input_scale * filter_scale.
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* bias_scale == input_scale * filter_scale. For filter tensor of
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* {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL}, the bias
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* must be of {@link OperandType::TENSOR_INT32}, with zeroPoint of
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* 0 and bias_scale of 0. The actual scale of each value 'i' is equal
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* to bias_scale[i] = input_scale * filter_scale[i].
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* * 3: An {@link OperandType::INT32} scalar, specifying the padding on
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* the left, in the ‘width’ dimension.
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* * 4: An {@link OperandType::INT32} scalar, specifying the padding on
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@@ -4252,14 +4269,20 @@ enum OperationType : int32_t {
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* specifying the input.
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* * 1: A 4-D tensor, of shape
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* [depth_out, filter_height, filter_width, depth_in], specifying the
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* filter.
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* filter. For tensor of type
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* {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL} the channel
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* dimension (extraParams.channelQuant.channelDim) must be set to 0.
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* * 2: A 1-D tensor, of shape [depth_out], specifying the bias. For input
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* tensor of type {@link OperandType::TENSOR_FLOAT32} or
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* {@link OperandType::TENSOR_FLOAT16}, the bias should be of the
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* same type. For input tensor of type
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* {@link OperandType::TENSOR_QUANT8_ASYMM}, the bias should be
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* of {@link OperandType::TENSOR_INT32}, with zeroPoint of 0 and
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* bias_scale == input_scale * filter_scale.
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* bias_scale == input_scale * filter_scale. For filter tensor of
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* {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL}, the bias
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* must be of {@link OperandType::TENSOR_INT32}, with zeroPoint of
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* 0 and bias_scale of 0. The actual scale of each value 'i' is equal
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* to bias_scale[i] = input_scale * filter_scale[i].
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* * 3: An {@link OperandType::TENSOR_INT32} tensor, specifying the output
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* tensor shape.
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* * 4: An {@link OperandType::INT32} scalar, specifying the implicit
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@@ -4279,7 +4302,9 @@ enum OperationType : int32_t {
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* * 0: The output 4-D tensor, of shape
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* [batches, out_height, out_width, depth_out]. For output tensor of
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* {@link OperandType::TENSOR_QUANT8_ASYMM}, the following condition
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* must be satisfied: output_scale > input_scale * filter_scale.
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* must be satisfied: output_scale > input_scale * filter_scale (for
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* filter tensor of {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL}
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* this condition must be true for all filter scales).
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*
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* Available since API level 29.
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*/
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