aboutsummaryrefslogtreecommitdiff
path: root/chapters/data_layout.adoc
diff options
context:
space:
mode:
Diffstat (limited to 'chapters/data_layout.adoc')
-rw-r--r--chapters/data_layout.adoc296
1 files changed, 296 insertions, 0 deletions
diff --git a/chapters/data_layout.adoc b/chapters/data_layout.adoc
new file mode 100644
index 0000000..8f318ae
--- /dev/null
+++ b/chapters/data_layout.adoc
@@ -0,0 +1,296 @@
+//
+// This confidential and proprietary software may be used only as
+// authorised by a licensing agreement from ARM Limited
+// (C) COPYRIGHT 2020 ARM Limited
+// ALL RIGHTS RESERVED
+// The entire notice above must be reproduced on all authorised
+// copies and copies may only be made to the extent permitted
+// by a licensing agreement from ARM Limited.
+
+=== Data Layout
+
+==== CONCAT
+Concatenate two tensors along a given axis. No data conversion happens during a concat operation.
+
+*Arguments:*
+
+|===
+|Argument|Type|Name|Shape|Description
+
+|Input|in_t*|input1|shape1|Input tensor from 1 to 4 dims
+|Input|in_t*|input2|shape2|Input tensor with rank matching input1
+|Attribute|int|axis|-|Axis along which concatenation is to occur.
+|Output|out_t*|output|shape|Output tensor of same type, size as the input tensor
+|===
+
+*Operation Function:*
+
+[source,c]
+----
+for_each (index1 in shape) {
+ index2 = index1
+ index2[axis] = index1[axis] - shape1[axis]
+ value = (index2[axis] < 0) ?
+ tensor_read<in_t>(input1, shape1, index1) :
+ tensor_read<in_t>(input2, shape2, index2) ;
+ tensor_write<in_t>(output, shape, index1, value);
+}
+----
+
+*Supported Data Types:*
+
+|===
+|Profile|Mode|in_t|out_t
+
+|Any|Boolean|bool|bool
+|Any|signed 8|int8/aint8|int8/aint8
+|Any|signed 16|int16|int16
+|Any|signed 32|int32|int32
+|MI, MT|float|float|float
+|===
+
+==== PAD
+
+Zero-pads a tensor along borders of each dimension.
+
+*Arguments:*
+
+|===
+|Argument|Type|Name|Shape|Description
+
+|Input|in_t*|input1|shape1|Input tensor
+|Attribute|int|padding|[rank(input1),2]|Amount of padding to be done
+|Output|out_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]
+----
+for_each (index in shape) {
+ index1 = index
+ for (i=0; i<dimensions(shape); i++) {
+ index1[i] = index1[i] - padding[i,0]
+ }
+ value = tensor_read<in_t>(input1, shape1, index1, input1_zp, padding)
+ tensor_write<in_t>(output, shape, index, value + input1_zp);
+}
+----
+
+*Supported Data Types:*
+
+|===
+|Profile|Mode|in_t|out_t
+
+|Any|Boolean|bool|bool
+|Any|signed 8|int8/aint8|int8/aint8
+|Any|signed 16|int16|int16
+|Any|signed 32|int32|int32
+|MI, MT|float|float|float
+|===
+
+==== RESHAPE
+
+Returns a tensor with the same type/values as the input, with a new shape specified by the shape argument. Reshape may operate on tensors of any rank. No data conversion happens during a reshape operation.
+
+*Arguments:*
+
+|===
+|Argument|Type|Name|Shape|Description
+
+|Input|in_t*|input1|shape1|Input tensor from 1 to 4 dims
+|Attribute|int|new_shape|[rank(output)]|List of values, with each element giving the size of the result tensor for the given dimension. At most one dimension may be given as-1 to automatically calculate the dimension size.
+|Output|out_t*|output|shape|Output tensor of same type, size as the input tensor
+|===
+
+*Operation Function:*
+
+[source,c]
+----
+assert(tensor_size(shape1)==tensor_size(shape))
+for (i=0; i<tensor_size(shape); i++) {
+ output[i] = input[i]
+}
+----
+
+*Supported Data Types:*
+
+|===
+|Profile|Mode|in_t|out_t
+
+|Any|Boolean|bool|bool
+|Any|signed 8|int8/aint8|int8/aint8
+|Any|signed 16|int16|int16
+|Any|signed 32|int32|int32
+|MI, MT|float|float|float
+|===
+
+==== REVERSE
+
+Returns a tensor with the same type/values as the input, with the data reversed along the given axes. No data conversion happens during a reverse operation.
+
+*Arguments:*
+
+|===
+|Argument|Type|Name|Shape|Description
+
+|Input|in_t*|input|shape|Input tensor from 1 to 4 dims
+|Attribute|int|axes|[]|List of axes along which to reverse with size from 1 to rank(input1). Values are integers into the 0-based dimensions of the input tensor. An empty list is not allowed.
+|Output|out_t*|output|shape|Output tensor of same type, size as the input tensor
+|===
+
+*Operation Function:*
+
+[source,c]
+----
+for_each (index in shape) {
+ tmp_index = index;
+ for_each (axis in axes[]) {
+ tmp_index[axis] = shape[axis]-1-index[axis]
+ }
+ value = tensor_read<in_t>(input, shape, tmp_index);
+ tensor_write<in_t>(output, shape, index, value);
+}
+----
+
+*Supported Data Types:*
+
+|===
+|Profile|Mode|in_t|out_t
+
+|Any|Boolean|bool|bool
+|Any|signed 8|int8/aint8|int8/aint8
+|Any|signed 16|int16|int16
+|Any|signed 32|int32|int32
+|MI, MT|float|float|float
+|===
+
+==== SLICE
+
+Extracts a slice of the input tensor 0 on the given axis, beginning at the start coordinates, and extending for size elements in each direction. No data conversion happens during a slice operation.
+
+*Arguments:*
+|===
+|Argument|Type|Name|Shape|Description
+
+|Input|in_t*|input1|shape1|Input tensor from 1 to 4 dims
+|Attribute|int|start|[rank(input1)]|List of integer coordinates, of length equal to the rank of input 0. Start coordinate for slicing.
+|Attribute|int|size|[rank(input1)]|List of integer size values, of length equal to the rank of input 0. Size of the input to be used.
+|Output|out_t*|output|shape|Output tensor of same type as the input tensor
+|===
+
+*Operation Function:*
+
+[source,c]
+----
+for_each (index in shape) {
+ tmp_index = index;
+ for (i=0; i<dimensions(shape); i++) {
+ tmp_index[i] = index[i] + start[i];
+ }
+ value = tensor_read<in_t>(input, shape1, tmp_index);
+ tensor_write<in_t>(output, shape, index, value);
+}
+----
+
+*Supported Data Types:*
+
+|===
+|Profile|Mode|in_t|out_t
+
+|Any|Boolean|bool|bool
+|Any|signed 8|int8/aint8|int8/aint8
+|Any|signed 16|int16|int16
+|Any|signed 32|int32|int32
+|MI, MT|float|float|float
+|===
+
+==== TILE
+
+Replicates input 0 multiplies times along each dimension.
+
+*Arguments:*
+
+|===
+|Argument|Type|Name|Shape|Description
+
+|Input|in_t*|input1|shape1|Input tensor from 1 to 4 dims
+|Attribute|int|multiplies|[rank(shape1)]|Number of times to replicate input1 in each dimension
+|Output|out_t*|output|shape|Output tensor of same type, rank as the input tensor
+|===
+
+*Operation Function:*
+
+[source,c]
+----
+for_each (index in shape) {
+ tmp_index = index;
+ for (i=0; i<dimensions(shape); i++) {
+ assert(shape1[i] * multiplies[i] == shape[i])
+ tmp_index[i] = index[i] % shape1[i]
+ }
+ value = tensor_read<in_t>(input, shape1, tmp_index);
+ tensor_write<in_t>(output, shape, index, value);
+}
+----
+
+*Supported Data Types:*
+
+|===
+|Profile|Mode|in_t|out_t
+
+|Any|Boolean|bool|bool
+|Any|signed 8|int8/aint8|int8/aint8
+|Any|signed 16|int16|int16
+|Any|signed 32|int32|int32
+|MI, MT|float|float|float
+|===
+
+==== TRANSPOSE
+
+Permutes the dimensions based on perm.
+
+*Arguments:*
+
+|===
+|Argument|Type|Name|Shape|Description
+
+|Input|in_t*|input1|shape1|Input tensor from 1 to 4 dims
+|Attribute|int|perms|[rank(input1)]|List of integers of length equal to the rank of input1.
+|Output|out_t*|output|shape|Output tensor of same type, rank as the input tensor
+|===
+
+*Operation Function:*
+
+[source,c]
+----
+for_each (index in shape) {
+ tmp_index = index;
+ for (i=0; i<dimensions(shape); i++) {
+ assert(shape1[perm[i]] == shape[i])
+ tmp_index[perm[i]] = index[i]
+ }
+ value = tensor_read<in_t>(input, shape1, tmp_index);
+ tensor_write<in_t>(output, shape, index, value);
+}
+----
+
+*Supported Data Types:*
+
+|===
+|Profile|Mode|in_t|out_t
+
+|Any|Boolean|bool|bool
+|Any|signed 8|int8/aint8|int8/aint8
+|Any|signed 16|int16|int16
+|Any|signed 32|int32|int32
+|MI, MT|float|float|float
+|===
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-12 05:26:08 +0000