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-rw-r--r--chapters/data_layout.adoc9
-rw-r--r--chapters/ewise_binary.adoc12
-rw-r--r--chapters/ewise_ternary.adoc4
-rw-r--r--chapters/ewise_unary.adoc19
-rw-r--r--chapters/image.adoc4
-rw-r--r--chapters/reduction.adoc4
-rw-r--r--chapters/scatter_gather.adoc4
-rw-r--r--chapters/tensor_ops.adoc85
-rw-r--r--chapters/type_conversion.adoc11
9 files changed, 19 insertions, 133 deletions
diff --git a/chapters/data_layout.adoc b/chapters/data_layout.adoc
index 4368474..bc8d853 100644
--- a/chapters/data_layout.adoc
+++ b/chapters/data_layout.adoc
@@ -68,17 +68,10 @@ Returns a new tensor with the padding included.
|Input|in_t*|input1|shape1|Input tensor
|Attribute|int|padding|[rank(input1),2]|Amount of padding to be done
|Attribute|in_t|pad_const|-|Constant value to be used as padding
+|Attribute|in_t|input1_zp|-|Input tensor zero point. Must be zero for non-int8 types.
|Output|in_t*|output|shape|Output tensor of same type as the input tensor
|===
-*Quantization Parameters:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Attribute|in_t|input1_zp|-|Input tensor zero point
-|===
-
*Operation Function:*
[source,c++]
diff --git a/chapters/ewise_binary.adoc b/chapters/ewise_binary.adoc
index 99eb597..f44f7f5 100644
--- a/chapters/ewise_binary.adoc
+++ b/chapters/ewise_binary.adoc
@@ -271,10 +271,6 @@ Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match
|Output|in_t*|output|shape|Output tensor with broadcast shape if necessary
|===
-*Quantization Parameters:*
-
-None
-
*Operation Function:*
[source,c++]
@@ -586,10 +582,6 @@ Axis of size 1 will be broadcast, as necessary. Rank of input tensors must match
|Output|in_t*|output|shape|Output tensor of same type as the input tensors, with broadcast shape if necessary
|===
-*Quantization Parameters:*
-
-Only supported with floating-point values.
-
*Supported Data Types:*
|===
@@ -662,10 +654,6 @@ An int16_t to int16_t table lookup can be constructed in TOSA as follows:
|Output|out_t*|output|shape|Output tensor
|===
-*Quantization Parameters:*
-
-None
-
*Operation Function:*
[source,c++]
diff --git a/chapters/ewise_ternary.adoc b/chapters/ewise_ternary.adoc
index e7f8c2e..ecf40d1 100644
--- a/chapters/ewise_ternary.adoc
+++ b/chapters/ewise_ternary.adoc
@@ -24,10 +24,6 @@ Elementwise select of the output based on a condition.
|Output|in_t*|output|shape|Output tensor of same type as input2 and input3, with broadcast shape if necessary
|===
-*Quantization Parameters:*
-
-None
-
*Operation Function:*
[source,c++]
diff --git a/chapters/ewise_unary.adoc b/chapters/ewise_unary.adoc
index 036c6e3..2dc01df 100644
--- a/chapters/ewise_unary.adoc
+++ b/chapters/ewise_unary.adoc
@@ -56,10 +56,6 @@ Elementwise bitwise NOT of input tensor.
|Output|in_t*|output|shape|Output tensor of same type, size as the input tensor
|===
-*Quantization Parameters:*
-
-None
-
*Operation Function:*
[source,c++]
@@ -210,10 +206,6 @@ Elementwise logical NOT of input.
|Output|in_t*|output|shape|Output tensor of same type, size as the input tensor
|===
-*Quantization Parameters:*
-
-None
-
*Operation Function:*
[source,c++]
@@ -243,18 +235,11 @@ Elementwise negation operation
|Argument|Type|Name|Shape|Description
|Input|in_t*|input1|shape|Input tensor
+|Attribute|in_t|input1_zp|-|Input 1 zero point. Must be zero for non-int8 types.
+|Attribute|in_t|output_zp|-|Output zero point. Must be zero for non-int8 types.
|Output|in_t*|output|shape|Output tensor of same type, size as the input tensor
|===
-*Quantization Parameters:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Attribute|in_t|input1_zp|-|Input 1 zero point
-|Attribute|in_t|output_zp|-|Output zero point
-|===
-
*Operation Function:*
[source,c++]
diff --git a/chapters/image.adoc b/chapters/image.adoc
index b8789ff..2491ea5 100644
--- a/chapters/image.adoc
+++ b/chapters/image.adoc
@@ -45,10 +45,6 @@ from the strides.
|Output|out_t*|output|[N,OH,OW,C]|Output tensor
|===
-*Quantization Parameters:*
-
-None
-
*Operation Function*
[source,c++]
diff --git a/chapters/reduction.adoc b/chapters/reduction.adoc
index c39fecf..b687896 100644
--- a/chapters/reduction.adoc
+++ b/chapters/reduction.adoc
@@ -148,10 +148,6 @@ Reduce a tensor along the given axis with a minimum operation
|Output|in_t*|output|shape|Output tensor. Same rank as the input tensor.
|===
-*Quantization Parameters:*
-
-Quantization is ignored when doing the REDUCE_MIN operation. The input and output must maintain the same parameters.
-
*Operation Function:*
[source,c]
diff --git a/chapters/scatter_gather.adoc b/chapters/scatter_gather.adoc
index 6fedb45..63f30dc 100644
--- a/chapters/scatter_gather.adoc
+++ b/chapters/scatter_gather.adoc
@@ -24,10 +24,6 @@ N is the number of batches, W the number of indices in each batch, K the range o
|Output|value_t*|output|[N,W,C]|3D output tensor
|===
-*Quantization Parameters:*
-
-None
-
*Operation Function:*
[source,c++]
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++]
diff --git a/chapters/type_conversion.adoc b/chapters/type_conversion.adoc
index b947b73..8619fc3 100644
--- a/chapters/type_conversion.adoc
+++ b/chapters/type_conversion.adoc
@@ -82,15 +82,8 @@ Rescale quantized values into a new domain. This function scales by factor: mult
|Input|in_t*|input|shape|Input tensor from 1 to 4 dims
|Output|out_t*|output|shape|Output tensor with the same shape as input
-|===
-
-*Quantization Parameters:*
-
-|===
-|Argument|Type|Name|Shape|Description
-
-|Attribute|in_t|input_zp|-|Input tensor zero point
-|Attribute|out_t|output_zp|-|Output tensor zero point
+|Attribute|in_t|input_zp|-|Input tensor zero point. Must be zero for non-int8 types.
+|Attribute|out_t|output_zp|-|Output tensor zero point. Must be zero for non-int8 types.
|Input (MT profile) Attribute (BI/MI profiles)|mul_t|multiplier[NC]|-|Scaling multiplier array
|Input (MT profile) Attribute (BI/MI profiles)|uint6_t|shift[NC] |-|Scaling shift array
|Attribute|bool_t|scale32|-|if (scale32) mul_t=int32_t else mul_t=int16_t
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-17 07:26:01 +0000