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diff --git a/tensorflow/contrib/lite/g3doc/tflite_convert/cmdline_reference.md b/tensorflow/contrib/lite/g3doc/tflite_convert/cmdline_reference.md new file mode 100644 index 0000000000..d65912fea6 --- /dev/null +++ b/tensorflow/contrib/lite/g3doc/tflite_convert/cmdline_reference.md @@ -0,0 +1,159 @@ +# TensorFlow Lite Converter command-line glossary + +This page is complete reference of command-line flags used by the TensorFlow +Lite Converter's command line starting from TensorFlow 1.9 up until the most +recent build of TensorFlow. + +[TOC] + +## High-level flags + +The following high level flags specify the details of the input and output +files. The flag `--output_file` is always required. Additionally, either +`--graph_def_file`, `--saved_model_dir` or `--keras_model_file` is required. + +* `--output_file`. Type: string. Specifies the full path of the output file. +* `--graph_def_file`. Type: string. Specifies the full path of the input + GraphDef file frozen using + [freeze_graph.py](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/tools/freeze_graph.py). +* `--saved_model_dir`. Type: string. Specifies the full path to the directory + containing the SavedModel. +* `--keras_model_file`. Type: string. Specifies the full path of the HDF5 file + containing the tf.keras model. +* `--output_format`. Type: string. Default: `TFLITE`. Specifies the format of + the output file. Allowed values: + * `TFLITE`: TensorFlow Lite FlatBuffer format. + * `GRAPHVIZ_DOT`: GraphViz `.dot` format containing a visualization of the + graph after graph transformations. + * Note that passing `GRAPHVIZ_DOT` to `--output_format` leads to loss + of TFLite specific transformations. Therefore, the resulting + visualization may not reflect the final set of graph + transformations. To get a final visualization with all graph + transformations use `--dump_graphviz_dir` instead. + +The following flags specify optional parameters when using SavedModels. + +* `--saved_model_tag_set`. Type: string. Default: + [kSavedModelTagServe](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/cc/saved_model/tag_constants.h). + Specifies a comma-separated set of tags identifying the MetaGraphDef within + the SavedModel to analyze. All tags in the tag set must be specified. +* `--saved_model_signature_key`. Type: string. Default: + [DEFAULT_SERVING_SIGNATURE_DEF_KEY](https://www.tensorflow.org/api_docs/python/tf/saved_model/signature_constants). + Specifies the key identifying the SignatureDef containing inputs and + outputs. + +## Model flags + +*Model flags* provide additional information about the model stored in the input +file. + +* `--input_arrays`. Type: comma-separated list of strings. Specifies the list + of names of input activation tensors. +* `--output_arrays`. Type: comma-separated list of strings. Specifies the list + of names of output activation tensors. + +The following flags define properties of the input tensors. Each item in the +`--input_arrays` flag should correspond to each item in the following flags +based on index. + +* `--input_shapes`. Type: colon-separated list of comma-separated lists of + integers. Each comma-separated list of integers gives the shape of one of + the input arrays specified in + [TensorFlow convention](https://www.tensorflow.org/guide/dims_types#shape). + * Example: `--input_shapes=1,60,80,3` for a typical vision model means a + batch size of 1, an input image height of 60, an input image width of + 80, and an input image depth of 3 (representing RGB channels). + * Example: `--input_arrays=foo,bar --input_shapes=2,3:4,5,6` means "foo" + has a shape of [2, 3] and "bar" has a shape of [4, 5, 6]. +* `--std_dev_values`, `--mean_values`. Type: comma-separated list of floats. + These specify the (de-)quantization parameters of the input array, when it + is quantized. This is only needed if `inference_input_type` is + `QUANTIZED_UINT8`. + * The meaning of `mean_values` and `std_dev_values` is as follows: each + quantized value in the quantized input array will be interpreted as a + mathematical real number (i.e. as an input activation value) according + to the following formula: + * `real_value = (quantized_input_value - mean_value) / std_dev_value`. + * When performing float inference (`--inference_type=FLOAT`) on a + quantized input, the quantized input would be immediately dequantized by + the inference code according to the above formula, before proceeding + with float inference. + * When performing quantized inference + (`--inference_type=QUANTIZED_UINT8`), no dequantization is performed by + the inference code. However, the quantization parameters of all arrays, + including those of the input arrays as specified by `mean_value` and + `std_dev_value`, determine the fixed-point multipliers used in the + quantized inference code. `mean_value` must be an integer when + performing quantized inference. + +## Transformation flags + +*Transformation flags* specify options of the transformations to be applied to +the graph, i.e. they specify requested properties that the output file should +have. + +* `--inference_type`. Type: string. Default: `FLOAT`. Data type of all + real-number arrays in the output file except for input arrays (defined by + `--inference_input_type`). Must be `{FLOAT, QUANTIZED_UINT8}`. + + This flag only impacts real-number arrays including float and quantized + arrays. This excludes all other data types including plain integer arrays + and string arrays. Specifically: + + * If `FLOAT`, then real-numbers arrays will be of type float in the output + file. If they were quantized in the input file, then they get + dequantized. + * If `QUANTIZED_UINT8`, then real-numbers arrays will be quantized as + uint8 in the output file. If they were float in the input file, then + they get quantized. + +* `--inference_input_type`. Type: string. Data type of a real-number input + array in the output file. By default the `--inference_type` is used as type + of all of the input arrays. Flag is primarily intended for generating a + float-point graph with a quantized input array. A Dequantized operator is + added immediately after the input array. Must be `{FLOAT, QUANTIZED_UINT8}`. + + The flag is typically used for vision models taking a bitmap as input but + requiring floating-point inference. For such image models, the uint8 input + is quantized and the quantization parameters used for such input arrays are + their `mean_value` and `std_dev_value` parameters. + +* `--default_ranges_min`, `--default_ranges_max`. Type: floating-point. + Default value for the (min, max) range values used for all arrays without a + specified range. Allows user to proceed with quantization of non-quantized + or incorrectly-quantized input files. These flags produce models with low + accuracy. They are intended for easy experimentation with quantization via + "dummy quantization". + +* `--drop_control_dependency`. Type: boolean. Default: True. Indicates whether + to drop control dependencies silently. This is due to TensorFlow Lite not + supporting control dependencies. + +* `--reorder_across_fake_quant`. Type: boolean. Default: False. Indicates + whether to reorder FakeQuant nodes in unexpected locations. Used when the + location of the FakeQuant nodes is preventing graph transformations + necessary to convert the graph. Results in a graph that differs from the + quantized training graph, potentially causing differing arithmetic behavior. + +* `--allow_custom_ops`. Type: string. Default: False. Indicates whether to + allow custom operations. When false, any unknown operation is an error. When + true, custom ops are created for any op that is unknown. The developer will + need to provide these to the TensorFlow Lite runtime with a custom resolver. + +* `--post_training_quantize`. Type: boolean. Default: False. Boolean + indicating whether to quantize the weights of the converted float model. + Model size will be reduced and there will be latency improvements (at the + cost of accuracy). + +## Logging flags + +The following flags generate graph visualizations of the graph as +[GraphViz](https://www.graphviz.org/) `.dot` files at various points during +graph transformations: + +* `--dump_graphviz_dir`. Type: string. Specifies the full path of the + directory to output GraphViz `.dot` files. Outputs the graph immediately + after reading in the graph and after all of the transformations have been + completed. +* `--dump_graphviz_video`. Type: boolean. Outputs GraphViz after every graph + transformation. Requires `--dump_graphviz_dir` to be specified. |