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Diffstat (limited to 'chapters/tensor_ops.adoc')
| -rw-r--r-- | chapters/tensor_ops.adoc | 85 |
1 files changed, 14 insertions, 71 deletions
diff --git a/chapters/tensor_ops.adoc b/chapters/tensor_ops.adoc index 16b0341..0b78c8f 100644 --- a/chapters/tensor_ops.adoc +++ b/chapters/tensor_ops.adoc @@ -23,10 +23,6 @@ This returns the index with the largest value across the given axis of the input |Output|out_t*|output|shape|Output tensor, with rank = rank(shape1)-1 |=== -*Quantization Parameters:* - -None - *Operation Function:* [source,c++] @@ -82,18 +78,11 @@ When calculating the average, only the number of valid input tensor values, but |Attribute|int*|kernel|[2]|[kernel_y, kernel_x] |Attribute|int*|stride|[2]|[stride_y, stride_x] |Attribute|int*|pad|[4]|[pad_top, pad_bottom, pad_left, pad_right] +|Attribute|in_t|input_zp|-|Input tensor zero point. Must be zero for non-int8 types. +|Attribute|in_t|output_zp|-|Output tensor zero point. Must be zero for non-int8 types. |Output|in_t*|output|[N,H,W,C]|Output tensor 4D |=== -*Quantization Parameters:* - -|=== -|Argument|Type|Name|Shape|Description - -|Attribute|in_t|input_zp|-|Input tensor zero point -|Attribute|in_t|output_zp|-|Output tensor zero point -|=== - *Operation Function:* [source,c++] @@ -161,18 +150,11 @@ Performs a 2D convolution over the given tensor input, using the weight tensor. |Attribute|int*|pad|[4]|[pad_top, pad_bottom, pad_left, pad_right] |Attribute|int*|stride|[2]|[stride_y, stride_x] |Attribute|int*|dilation|[2]|[dilation_y, dilation_x] +|Attribute|in_t|input_zp|-|Input tensor zero point. Must be zero for non-int8 types. +|Attribute|weight_t|weight_zp|-|Weight zero point. Must be zero for non-int8 types. |Output|acc_t*|output|[N,H,W,OC]|Output tensor |=== -*Quantization Parameters:* - -|=== -|Argument|Type|Name|Shape|Description - -|Attribute|in_t|input_zp|-|Input tensor zero point -|Attribute|weight_t|weight_zp|-|Weight zero point -|=== - *Operation Function* [source,c++] @@ -227,18 +209,11 @@ Performs a 3D convolution over the given input tensor. |Attribute|int*|pad|[6]|[pad_d0, pad_d1, pad_top, pad_bottom, pad_left, pad_right] |Attribute|int*|stride|[3]|[stride_d, stride_y, stride_x] |Attribute|int*|dilation|[3]|[dilation_d, dilation_y, dilation_x] +|Attribute|in_t|input_zp|-|Input tensor zero point. Must be zero for non-int8 types. +|Attribute|weight_t|weight_zp|-|Weight zero point. Must be zero for non-int8 types. |Output|acc_t*|output|[N,D,H,W,OC]|Output tensor |=== -*Quantization Parameters:* - -|=== -|Argument|Type|Name|Shape|Description - -|Attribute|in_t|input_zp|-|Input tensor zero point -|Attribute|weight_t|weight_zp|-|Weight zero point -|=== - *Operation Function* [source,c++] @@ -296,18 +271,11 @@ Performs 2D convolutions separately over each channel of the given tensor input, |Attribute|int*|pad|[4]|[pad_top, pad_bottom, pad_left, pad_right] |Attribute|int*|stride|[2]|[stride_y, stride_x] |Attribute|int*|dilation|[2]|[dilation_y, dilation_x] +|Attribute|in_t|input_zp|-|Input tensor zero point. Must be zero for non-int8 types. +|Attribute|weight_t|weight_zp|-|Weight zero point. Must be zero for non-int8 types. |Output|acc_t*|output|[N,H,W,C*M]|Output tensor |=== -*Quantization Parameters:* - -|=== -|Argument|Type|Name|Shape|Description - -|Attribute|in_t|input_zp|-|Input tensor zero point -|Attribute|weight_t|weight_zp|-|Weight zero point -|=== - *Operation Function* [source,c++] @@ -359,18 +327,11 @@ Performs a fully connected network. |Input|in_t*|input|[N,IC]|Input tensor |Attribute|weight_t*|weight|[OC,IC]|Weights |Attribute|acc_t*|bias|[OC]|Per output channel bias data. +|Attribute|in_t|input_zp|-|Input tensor zero point. Must be zero for non-int8 types. +|Attribute|weight_t|weight_zp|-|Weight zero point. Must be zero for non-int8 types. |Output|acc_t*|output|[N,OC]|Output tensor |=== -*Quantization Parameters:* - -|=== -|Argument|Type|Name|Shape|Description - -|Attribute|in_t|input_zp|-|Input tensor zero point -|Attribute|weight_t|weight_zp|-|Weight zero point -|=== - *Operation Function* [source,c++] @@ -410,18 +371,11 @@ Performs two dimensional matrix multiplications. This allows both inputs to be a |Input|in_t*|A|[N,H,C]|Input tensor A, N matrices of size HxC |Input|in_t*|B|[N,C,W]|Input tensor B, N matrices of size CxW +|Attribute|in_t|A_zp|-|Input tensor A zero point. Must be zero for non-int8 types. +|Attribute|in_t|B_zp|-|Input tensor B zero point. Must be zero for non-int8 types. |Output|acc_t*|output|[N,H,W]|Output tensor, N matrices of size HxW |=== -*Quantization Parameters:* - -|=== -|Argument|Type|Name|Shape|Description - -|Attribute|in_t|A_zp|-|Input tensor A zero point -|Attribute|in_t|B_zp|-|Input tensor B zero point -|=== - *Operation Function* [source,c++] @@ -463,10 +417,6 @@ This performs a max pooling over the given input tensor. A sliding window of siz |Output|in_t*|output|[N,H,W,C]|Output tensor 4D |=== -*Quantization Parameters:* - -None - *Operation Function:* [source,c++] @@ -521,18 +471,11 @@ Performs a 2D transposed convolution over the given tensor input, using the weig |Attribute|int*|out_pad|[2]|[out_pad_top, out_pad_left] |Attribute|int*|stride|[2]|[stride_y, stride_x] |Attribute|int*|out_shape|[4]|[N,OH,OW,OC] +|Attribute|in_t|input_zp|-|Input tensor zero point. Must be zero for non-int8 types. +|Attribute|weight_t|weight_zp|-|Weight zero point. Must be zero for non-int8 types. |Output|acc_t*|output|[N,OH,OW,OC]|Output tensor |=== -*Quantization Parameters:* - -|=== -|Argument|Type|Name|Shape|Description - -|Attribute|in_t|input_zp|-|Input tensor zero point -|Attribute|weight_t|weight_zp|-|Weight zero point -|=== - *Operation Function* [source,c++] |