translate latency (#143)

docs/en/api_en/index_en.rst

@@ -17,3 +17,4 @@ API Documents
    paddleslim.nas.one_shot.rst
    paddleslim.pantheon.rst
    search_space_en.rst
+   table_latency_en.md

docs/en/api_en/table_latency_en.md

+# Table about hardware lantency
+
+The table about hardware latency is used to evaluate the inference time in special environment and inference engine. The following text used to introduce the format that PaddleSlim support.
+
+## Introduce
+
+The table about hardware latency saved all possible operations, one operation in the table including type and parameters, such as: type can be `conv2d`, and corresponding parameters can be the size of feature map, number of kernel, and the size of kernel.
+The latency of every operation depends on hardware and inference engine.
+
+## Overview format
+The table about hardware latency saved in the way of file or multi-line string.
+The first line of the table about hardware latency saved the information about version, every line in the following represents a operation and its latency.
+
+## Version
+
+The information about version split by comma in the english format, and the detail is hardware, inference engine and timestamp.
+
+- ** hardware: ** Used to mark the environment of hardware, including type of architecture, version and so on.
+
+- ** inference engine: ** Used to mark inference engine, including the name of inference engine, version, optimize options and so on.
+
+- ** timestamp: ** Used to mark the time of this table created.
+
+## Operation
+
+The information about operation split by comma in the english format, the information about operation and latency split by tabs.
+
+### conv2d
+
+**format**
+
+```text
+op_type,flag_bias,flag_relu,n_in,c_in,h_in,w_in,c_out,groups,kernel,padding,stride,dilation\tlatency
+```
+
+**introduce**
+
+- **op_type(str)** - The type of this op.
+- **flag_bias (int)** - Whether has bias or not(0: donot has bias, 1: has bias).
+- **flag_relu (int)** - Whether has relu or not(0: donot has relu, 1: has relu).
+- **n_in (int)** - The batch size of input.
+- **c_in (int)** - The number of channel about input.
+- **h_in (int)** - The height of input feature map.
+- **w_in (int)** - The width of input feature map.
+- **c_out (int)** - The number of channel about output.
+- **groups (int)** - The group of conv2d.
+- **kernel (int)** - The size of kernel.
+- **padding (int)** - The size of padding.
+- **stride (int)** - The size of stride.
+- **dilation (int)** - The size of dilation.
+- **latency (float)** - The latency of this op.
+
+### activaiton
+
+**format**
+
+```text
+op_type,n_in,c_in,h_in,w_in\tlatency
+```
+
+**introduce**
+
+- **op_type(str)** - The type of this op.
+- **n_in (int)** - The batch size of input.
+- **c_in (int)** - The number of channel about input.
+- **h_in (int)** - The height of input feature map.
+- **w_in (int)** - The width of input feature map.
+- **latency (float)** - The latency of this op.
+
+### batch_norm
+
+**format**
+
+```text
+op_type,active_type,n_in,c_in,h_in,w_in\tlatency
+```
+
+**introduce**
+
+- **op_type(str)** - The type of this op.
+- **active_type (string|None)** - The type of activation function, including relu, prelu, sigmoid, relu6, tanh.
+- **n_in (int)** - The batch size of input.
+- **c_in (int)** - The number of channel about input.
+- **h_in (int)** - The height of input feature map.
+- **w_in (int)** - The width of input feature map.
+- **latency (float)** - The latency of this op.
+
+### eltwise
+
+**format**
+
+```text
+op_type,n_in,c_in,h_in,w_in\tlatency
+```
+
+**introduce**
+
+- **op_type(str)** - The type of this op.
+- **n_in (int)** - The batch size of input.
+- **c_in (int)** - The number of channel about input.
+- **h_in (int)** - The height of input feature map.
+- **w_in (int)** - The width of input feature map.
+- **latency (float)** - The latency of this op.
+
+### pooling
+
+**format**
+
+```text
+op_type,flag_global_pooling,n_in,c_in,h_in,w_in,kernel,padding,stride,ceil_mode,pool_type\tlatency
+```
+
+**introduce**
+
+- **op_type(str)** - The type of this op.
+- **flag_global_pooling (int)** - Whether is global pooling or not(0: is not global, 1: is global pooling).
+- **n_in (int)** - The batch size of input.
+- **c_in (int)** - The number of channel about input.
+- **h_in (int)** - The height of input feature map.
+- **w_in (int)** - The width of input feature map.
+- **kernel (int)** - The size of kernel.
+- **padding (int)** - The size of padding.
+- **stride (int)** - The size of stride.
+- **ceil_mode (int)** - Whether to compute height and width by using ceil function(0: use floor function, 1: use ceil function).
+- **pool_type (int)** - The type of pooling(1: max pooling 2: average pooling including padding 3: average pooling excluding padding).
+- **latency (float)** - The latency of this op.
+
+### softmax
+
+**format**
+
+```text
+op_type,axis,n_in,c_in,h_in,w_in\tlatency
+```
+
+**introduce**
+
+- **op_type(str)** - The type of this op.
+- **axis (int)** - The index to compute softmax, index in the range of [-1, rank-1], `rank` is the rank of input.
+- **n_in (int)** - The batch size of input.
+- **c_in (int)** - The number of channel about input.
+- **h_in (int)** - The height of input feature map.
+- **w_in (int)** - The width of input feature map.
+- **latency (float)** - The latency of this op.