diff options
Diffstat (limited to 'chapters/data_layout.adoc')
| -rw-r--r-- | chapters/data_layout.adoc | 68 |
1 files changed, 34 insertions, 34 deletions
diff --git a/chapters/data_layout.adoc b/chapters/data_layout.adoc index 54221f6..e50a14e 100644 --- a/chapters/data_layout.adoc +++ b/chapters/data_layout.adoc @@ -18,9 +18,9 @@ No data conversion happens during a concat operation. |=== |Argument|Type|Name|Shape|Description -|Input|in_t*|input1|shapes1[]|List of input tensors. All inputs must have the same rank and data type +|Input|in_out_t*|input1|shapes1[]|List of input tensors. All inputs must have the same rank and data type |Attribute|int|axis|-|Axis along which concatenation is to occur, in range from 0 to rank(shape)-1 -|Output|in_t*|output|shape|Output tensor +|Output|in_out_t*|output|shape|Output tensor |=== *Operation Function:* @@ -43,8 +43,8 @@ for_each(index1 in shape) { // For each output location, we are looking for the // appropriate input tensor if (index2[axis] >= 0 && index2[axis] < shapes1[t][axis]) { - in_t value = tensor_read<in_t>(input1[t], shapes1[t], index2); - tensor_write<in_t>(output, shape, index1, value); + in_out_t value = tensor_read<in_out_t>(input1[t], shapes1[t], index2); + tensor_write<in_out_t>(output, shape, index1, value); } index2[axis] = index2[axis] - shapes1[t][axis]; } @@ -55,7 +55,7 @@ for_each(index1 in shape) { *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |Any|Boolean|bool_t |Any|signed 8|int8_t @@ -75,10 +75,10 @@ The pad_const value includes the zero point if the tensor uses a zero point. |=== |Argument|Type|Name|Shape|Description -|Input|in_t*|input1|shape1|Input tensor +|Input|in_out_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 -|Output|in_t*|output|shape|Output tensor of same type as the input tensor +|Attribute|in_out_t|pad_const|-|Constant value to be used as padding +|Output|in_out_t*|output|shape|Output tensor of same type as the input tensor |=== *Operation Function:* @@ -98,15 +98,15 @@ for_each(index in shape) { is_pad = true; } } - in_t value = is_pad ? pad_const : tensor_read<in_t>(input1, shape1, index1); - tensor_write<in_t>(output, shape, index, value); + in_out_t value = is_pad ? pad_const : tensor_read<in_out_t>(input1, shape1, index1); + tensor_write<in_out_t>(output, shape, index, value); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |Any|Boolean|bool_t |Any|signed 8|int8_t @@ -124,9 +124,9 @@ Returns a tensor with the same type/values as the input, with a new shape specif |=== |Argument|Type|Name|Shape|Description -|Input|in_t*|input1|shape1|Input tensor +|Input|in_out_t*|input1|shape1|Input tensor |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|in_t*|output|shape|Output tensor of same type, size as the input tensor +|Output|in_out_t*|output|shape|Output tensor of same type, size as the input tensor |=== *Operation Function:* @@ -142,7 +142,7 @@ for(i = 0; i < tensor_size(shape); i++) { *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |Any|Boolean|bool_t |Any|signed 8|int8_t @@ -160,9 +160,9 @@ Returns a tensor with the same type/values as the input, with the data reversed |=== |Argument|Type|Name|Shape|Description -|Input|in_t*|input|shape|Input tensor from 1 to 4 dims +|Input|in_out_t*|input|shape|Input tensor from 1 to 4 dims |Attribute|int|axis|-|Axis to reverse, in range from 0 to rank(shape)-1 -|Output|in_t*|output|shape|Output tensor. Same shape as input tensor. +|Output|in_out_t*|output|shape|Output tensor. Same shape as input tensor. |=== *Operation Function:* @@ -173,15 +173,15 @@ ERROR_IF(axis < 0 || axis >= rank(shape)); for_each(index in shape) { tmp_index = index; tmp_index[axis] = shape[axis] - 1 - index[axis]; - in_t value = tensor_read<in_t>(input, shape, tmp_index); - tensor_write<in_t>(output, shape, index, value); + in_out_t value = tensor_read<in_out_t>(input, shape, tmp_index); + tensor_write<in_out_t>(output, shape, index, value); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |Any|Boolean|bool_t |Any|signed 8|int8_t @@ -199,10 +199,10 @@ No data conversion happens during a slice operation. |=== |Argument|Type|Name|Shape|Description -|Input|in_t*|input1|shape1|Input tensor with rank from 1 to 4 +|Input|in_out_t*|input1|shape1|Input tensor with rank from 1 to 4 |Attribute|int|start|[rank(input1)]|List of integer coordinates, of length equal to the rank of input1. Start coordinate for slicing. |Attribute|int|size|[rank(input1)]|List of integer size values, of length equal to the rank of input1. Size of the input to be used. -|Output|in_t*|output|shape|Output tensor of same type as the input tensor +|Output|in_out_t*|output|shape|Output tensor of same type as the input tensor |=== *Operation Function:* @@ -225,15 +225,15 @@ for_each(index in shape) { for(i = 0; i < rank(shape); i++) { tmp_index[i] = index[i] + start[i]; } - in_t value = tensor_read<in_t>(input, shape1, tmp_index); - tensor_write<in_t>(output, shape, index, value); + in_out_t value = tensor_read<in_out_t>(input, shape1, tmp_index); + tensor_write<in_out_t>(output, shape, index, value); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |Any|Boolean|bool_t |Any|signed 8|int8_t @@ -251,9 +251,9 @@ Replicates input1 multiplies times along each dimension. |=== |Argument|Type|Name|Shape|Description -|Input|in_t*|input1|shape1|Input tensor with rank from 1 to 4 +|Input|in_out_t*|input1|shape1|Input tensor with rank from 1 to 4 |Attribute|int32_t|multiplies|[rank(shape1)]|Number of times to replicate input1 in each dimension -|Output|in_t*|output|shape|Output tensor of same type, rank as the input tensor +|Output|in_out_t*|output|shape|Output tensor of same type, rank as the input tensor |=== *Operation Function:* @@ -266,15 +266,15 @@ for_each(index in shape) { REQUIRE(shape1[i] * multiplies[i] == shape[i]); tmp_index[i] = index[i] % shape1[i]; } - in_t value = tensor_read<in_t>(input, shape1, tmp_index); - tensor_write<in_t>(output, shape, index, value); + in_out_t value = tensor_read<in_out_t>(input, shape1, tmp_index); + tensor_write<in_out_t>(output, shape, index, value); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |Any|Boolean|bool_t |Any|signed 8|int8_t @@ -292,9 +292,9 @@ Permutes the dimensions based on perm. |=== |Argument|Type|Name|Shape|Description -|Input|in_t*|input1|shape1|Input tensor with minimum rank of one. +|Input|in_out_t*|input1|shape1|Input tensor with minimum rank of one. |Attribute|int32_t|perms|[rank(input1)]|List of integers of length equal to the rank of input1. Values must be valid dimensions within shape1, and may not be repeated. -|Output|in_t*|output|shape|Output tensor of same type, rank as the input tensor +|Output|in_out_t*|output|shape|Output tensor of same type, rank as the input tensor |=== *Operation Function:* @@ -315,15 +315,15 @@ for_each(index in shape) { REQUIRE(shape1[perm[i]] == shape[i]) tmp_index[perm[i]] = index[i] } - in_t value = tensor_read<in_t>(input, shape1, tmp_index); - tensor_write<in_t>(output, shape, index, value); + in_out_t value = tensor_read<in_out_t>(input, shape1, tmp_index); + tensor_write<in_out_t>(output, shape, index, value); } ---- *Supported Data Types:* |=== -|Profile|Mode|in_t +|Profile|Mode|in_out_t |Any|Boolean|bool_t |Any|signed 8|int8_t |