tensorflow/contrib/lite/build_def.bzl - platform/external/tensorflow - Git at Google

 """Generate Flatbuffer binary from json."""

 load(
     "//tensorflow:tensorflow.bzl",
     "tf_cc_shared_object",
     "tf_cc_test",
 )

 def tflite_copts():
     """Defines compile time flags."""
     copts = [
         "-DFARMHASH_NO_CXX_STRING",
     ] + select({
         str(Label("//tensorflow:android_arm64")): [
             "-std=c++11",
             "-O3",
         ],
         str(Label("//tensorflow:android_arm")): [
             "-mfpu=neon",
             "-mfloat-abi=softfp",
             "-std=c++11",
             "-O3",
         ],
         str(Label("//tensorflow:android_x86")): [
             "-DGEMMLOWP_ALLOW_SLOW_SCALAR_FALLBACK",
         ],
         str(Label("//tensorflow:ios_x86_64")): [
             "-msse4.1",
         ],
         str(Label("//tensorflow:windows")): [
             "/DTF_COMPILE_LIBRARY",
         ],
         "//conditions:default": [],
     }) + select({
         str(Label("//tensorflow:with_default_optimizations")): [],
         "//conditions:default": ["-DGEMMLOWP_ALLOW_SLOW_SCALAR_FALLBACK"],
     })

     return copts

 LINKER_SCRIPT = "//tensorflow/contrib/lite/java/src/main/native:version_script.lds"

 def tflite_linkopts_unstripped():
     """Defines linker flags to reduce size of TFLite binary.

        These are useful when trying to investigate the relative size of the
        symbols in TFLite.

     Returns:
        a select object with proper linkopts
     """

     # In case you wonder why there's no --icf is because the gains were
     # negligible, and created potential compatibility problems.
     return select({
         "//tensorflow:android": [
             "-Wl,--no-export-dynamic",  # Only inc syms referenced by dynamic obj.
             "-Wl,--exclude-libs,ALL",  # Exclude syms in all libs from auto export.
             "-Wl,--gc-sections",  # Eliminate unused code and data.
             "-Wl,--as-needed",  # Don't link unused libs.
         ],
         "//conditions:default": [],
     })

 def tflite_jni_linkopts_unstripped():
     """Defines linker flags to reduce size of TFLite binary with JNI.

        These are useful when trying to investigate the relative size of the
        symbols in TFLite.

     Returns:
        a select object with proper linkopts
     """

     # In case you wonder why there's no --icf is because the gains were
     # negligible, and created potential compatibility problems.
     return select({
         "//tensorflow:android": [
             "-Wl,--gc-sections",  # Eliminate unused code and data.
             "-Wl,--as-needed",  # Don't link unused libs.
         ],
         "//conditions:default": [],
     })

 def tflite_linkopts():
     """Defines linker flags to reduce size of TFLite binary."""
     return tflite_linkopts_unstripped() + select({
         "//tensorflow:android": [
             "-s",  # Omit symbol table.
         ],
         "//conditions:default": [],
     })

 def tflite_jni_linkopts():
     """Defines linker flags to reduce size of TFLite binary with JNI."""
     return tflite_jni_linkopts_unstripped() + select({
         "//tensorflow:android": [
             "-s",  # Omit symbol table.
             "-latomic",  # Required for some uses of ISO C++11 <atomic> in x86.
         ],
         "//conditions:default": [],
     })

 def tflite_jni_binary(
         name,
         copts = tflite_copts(),
         linkopts = tflite_jni_linkopts(),
         linkscript = LINKER_SCRIPT,
         linkshared = 1,
         linkstatic = 1,
         deps = []):
     """Builds a jni binary for TFLite."""
     linkopts = linkopts + [
         "-Wl,--version-script",  # Export only jni functions & classes.
         "$(location {})".format(linkscript),
     ]
     native.cc_binary(
         name = name,
         copts = copts,
         linkshared = linkshared,
         linkstatic = linkstatic,
         deps = deps + [linkscript],
         linkopts = linkopts,
     )

 def tflite_cc_shared_object(
         name,
         copts = tflite_copts(),
         linkopts = [],
         linkstatic = 1,
         deps = []):
     """Builds a shared object for TFLite."""
     tf_cc_shared_object(
         name = name,
         copts = copts,
         linkstatic = linkstatic,
         linkopts = linkopts + tflite_jni_linkopts(),
         framework_so = [],
         deps = deps,
     )

 def tf_to_tflite(name, src, options, out):
     """Convert a frozen tensorflow graphdef to TF Lite's flatbuffer.

     Args:
       name: Name of rule.
       src: name of the input graphdef file.
       options: options passed to TOCO.
       out: name of the output flatbuffer file.
     """

     toco_cmdline = " ".join([
         "//tensorflow/contrib/lite/toco:toco",
         "--input_format=TENSORFLOW_GRAPHDEF",
         "--output_format=TFLITE",
         ("--input_file=$(location %s)" % src),
         ("--output_file=$(location %s)" % out),
     ] + options)
     native.genrule(
         name = name,
         srcs = [src],
         outs = [out],
         cmd = toco_cmdline,
         tools = ["//tensorflow/contrib/lite/toco:toco"],
     )

 def tflite_to_json(name, src, out):
     """Convert a TF Lite flatbuffer to JSON.

     Args:
       name: Name of rule.
       src: name of the input flatbuffer file.
       out: name of the output JSON file.
     """

     flatc = "@flatbuffers//:flatc"
     schema = "//tensorflow/contrib/lite/schema:schema.fbs"
     native.genrule(
         name = name,
         srcs = [schema, src],
         outs = [out],
         cmd = ("TMP=`mktemp`; cp $(location %s) $${TMP}.bin &&" +
                "$(location %s) --raw-binary --strict-json -t" +
                " -o /tmp $(location %s) -- $${TMP}.bin &&" +
                "cp $${TMP}.json $(location %s)") %
               (src, flatc, schema, out),
         tools = [flatc],
     )

 def json_to_tflite(name, src, out):
     """Convert a JSON file to TF Lite's flatbuffer.

     Args:
       name: Name of rule.
       src: name of the input JSON file.
       out: name of the output flatbuffer file.
     """

     flatc = "@flatbuffers//:flatc"
     schema = "//tensorflow/contrib/lite/schema:schema_fbs"
     native.genrule(
         name = name,
         srcs = [schema, src],
         outs = [out],
         cmd = ("TMP=`mktemp`; cp $(location %s) $${TMP}.json &&" +
                "$(location %s) --raw-binary --unknown-json --allow-non-utf8 -b" +
                " -o /tmp $(location %s) $${TMP}.json &&" +
                "cp $${TMP}.bin $(location %s)") %
               (src, flatc, schema, out),
         tools = [flatc],
     )

 # This is the master list of generated examples that will be made into tests. A
 # function called make_XXX_tests() must also appear in generate_examples.py.
 # Disable a test by commenting it out. If you do, add a link to a bug or issue.
 def generated_test_models():
     return [
         "add",
         "arg_min_max",
         "avg_pool",
         "batch_to_space_nd",
         "concat",
         "constant",
         "control_dep",
         "conv",
         "conv_with_shared_weights",
         "conv_to_depthwiseconv_with_shared_weights",
         "depthwiseconv",
         "div",
         "equal",
         "exp",
         "expand_dims",
         "floor",
         "floor_div",
         "fully_connected",
         "fused_batch_norm",
         "gather",
         "global_batch_norm",
         "greater",
         "greater_equal",
         "sum",
         "l2norm",
         "l2_pool",
         "less",
         "less_equal",
         "local_response_norm",
         "log_softmax",
         "log",
         "logical_and",
         "logical_or",
         "logical_xor",
         "lstm",
         "max_pool",
         "maximum",
         "mean",
         "minimum",
         "mul",
         "neg",
         "not_equal",
         "one_hot",
         "pack",
         "pad",
         "padv2",
         "prelu",
         "pow",
         "reduce_any",
         "reduce_max",
         "reduce_min",
         "reduce_prod",
         "relu",
         "relu1",
         "relu6",
         "reshape",
         "resize_bilinear",
         "rsqrt",
         "shape",
         "sigmoid",
         "sin",
         "slice",
         "softmax",
         "space_to_batch_nd",
         "space_to_depth",
         "sparse_to_dense",
         "split",
         "sqrt",
         "square",
         "squeeze",
         "strided_slice",
         "strided_slice_1d_exhaustive",
         "sub",
         "tile",
         "topk",
         "transpose",
         #"transpose_conv",   # disabled due to b/111213074
         "unpack",
         "where",
         "zeros_like",
     ]

 def generated_test_conversion_modes():
     """Returns a list of conversion modes."""

     # TODO(nupurgarg): Add "pb2lite" when it's in open source. b/113614050.
     return ["toco-extended", ""]

 def generated_test_models_all():
     """Generates a list of all tests with the different converters.

     Returns:
       List of tuples representing (conversion mode, name of test).
     """
     conversion_modes = generated_test_conversion_modes()
     tests = generated_test_models()
     options = []
     for conversion_mode in conversion_modes:
         for test in tests:
             if conversion_mode:
                 test += "_%s" % conversion_mode
             options.append((conversion_mode, test))
     return options

 def gen_zip_test(name, test_name, conversion_mode, **kwargs):
     """Generate a zipped-example test and its dependent zip files.

     Args:
       name: str. Resulting cc_test target name
       test_name: str. Test targets this model. Comes from the list above.
       conversion_mode: str. Which conversion mode to run with. Comes from the
         list above.
       **kwargs: tf_cc_test kwargs
     """
     toco = "//tensorflow/contrib/lite/toco:toco"
     flags = ""
     if conversion_mode:
         # TODO(nupurgarg): Comment in when pb2lite is in open source. b/113614050.
         # if conversion_mode == "pb2lite":
         #     toco = "//tensorflow/contrib/lite/experimental/pb2lite:pb2lite"
         flags = "--ignore_toco_errors --run_with_extended"
         kwargs["tags"].append("skip_already_failing")
         kwargs["tags"].append("no_oss")
         kwargs["tags"].append("notap")

     gen_zipped_test_file(
         name = "zip_%s" % test_name,
         file = "%s.zip" % test_name,
         toco = toco,
         flags = flags,
     )
     tf_cc_test(name, **kwargs)

 def gen_zipped_test_file(name, file, toco, flags):
     """Generate a zip file of tests by using :generate_examples.

     Args:
       name: str. Name of output. We will produce "`file`.files" as a target.
       file: str. The name of one of the generated_examples targets, e.g. "transpose"
       toco: str. Pathname of toco binary to run
       flags: str. Any additional flags to include
     """
     native.genrule(
         name = file + ".files",
         cmd = (("$(locations :generate_examples) --toco $(locations {0}) " +
                 " --zip_to_output {1} {2} $(@D)").format(toco, file, flags)),
         outs = [file],
         tools = [
             ":generate_examples",
             toco,
         ],
     )

     native.filegroup(
         name = name,
         srcs = [file],
     )

 def gen_selected_ops(name, model):
     """Generate the library that includes only used ops.

     Args:
       name: Name of the generated library.
       model: TFLite model to interpret.
     """
     out = name + "_registration.cc"
     tool = "//tensorflow/contrib/lite/tools:generate_op_registrations"
     tflite_path = "//tensorflow/contrib/lite"
     native.genrule(
         name = name,
         srcs = [model],
         outs = [out],
         cmd = ("$(location %s) --input_model=$(location %s) --output_registration=$(location %s) --tflite_path=%s") %
               (tool, model, out, tflite_path[2:]),
         tools = [tool],
     )
	"""Generate Flatbuffer binary from json."""

	load(
	"//tensorflow:tensorflow.bzl",
	"tf_cc_shared_object",
	"tf_cc_test",
	)

	def tflite_copts():
	"""Defines compile time flags."""
	copts = [
	"-DFARMHASH_NO_CXX_STRING",
	] + select({
	str(Label("//tensorflow:android_arm64")): [
	"-std=c++11",
	"-O3",
	],
	str(Label("//tensorflow:android_arm")): [
	"-mfpu=neon",
	"-mfloat-abi=softfp",
	"-std=c++11",
	"-O3",
	],
	str(Label("//tensorflow:android_x86")): [
	"-DGEMMLOWP_ALLOW_SLOW_SCALAR_FALLBACK",
	],
	str(Label("//tensorflow:ios_x86_64")): [
	"-msse4.1",
	],
	str(Label("//tensorflow:windows")): [
	"/DTF_COMPILE_LIBRARY",
	],
	"//conditions:default": [],
	}) + select({
	str(Label("//tensorflow:with_default_optimizations")): [],
	"//conditions:default": ["-DGEMMLOWP_ALLOW_SLOW_SCALAR_FALLBACK"],
	})

	return copts

	LINKER_SCRIPT = "//tensorflow/contrib/lite/java/src/main/native:version_script.lds"

	def tflite_linkopts_unstripped():
	"""Defines linker flags to reduce size of TFLite binary.

	These are useful when trying to investigate the relative size of the
	symbols in TFLite.

	Returns:
	a select object with proper linkopts
	"""

	# In case you wonder why there's no --icf is because the gains were
	# negligible, and created potential compatibility problems.
	return select({
	"//tensorflow:android": [
	"-Wl,--no-export-dynamic", # Only inc syms referenced by dynamic obj.
	"-Wl,--exclude-libs,ALL", # Exclude syms in all libs from auto export.
	"-Wl,--gc-sections", # Eliminate unused code and data.
	"-Wl,--as-needed", # Don't link unused libs.
	],
	"//conditions:default": [],
	})

	def tflite_jni_linkopts_unstripped():
	"""Defines linker flags to reduce size of TFLite binary with JNI.

	These are useful when trying to investigate the relative size of the
	symbols in TFLite.

	Returns:
	a select object with proper linkopts
	"""

	# In case you wonder why there's no --icf is because the gains were
	# negligible, and created potential compatibility problems.
	return select({
	"//tensorflow:android": [
	"-Wl,--gc-sections", # Eliminate unused code and data.
	"-Wl,--as-needed", # Don't link unused libs.
	],
	"//conditions:default": [],
	})

	def tflite_linkopts():
	"""Defines linker flags to reduce size of TFLite binary."""
	return tflite_linkopts_unstripped() + select({
	"//tensorflow:android": [
	"-s", # Omit symbol table.
	],
	"//conditions:default": [],
	})

	def tflite_jni_linkopts():
	"""Defines linker flags to reduce size of TFLite binary with JNI."""
	return tflite_jni_linkopts_unstripped() + select({
	"//tensorflow:android": [
	"-s", # Omit symbol table.
	"-latomic", # Required for some uses of ISO C++11 <atomic> in x86.
	],
	"//conditions:default": [],
	})

	def tflite_jni_binary(
	name,
	copts = tflite_copts(),
	linkopts = tflite_jni_linkopts(),
	linkscript = LINKER_SCRIPT,
	linkshared = 1,
	linkstatic = 1,
	deps = []):
	"""Builds a jni binary for TFLite."""
	linkopts = linkopts + [
	"-Wl,--version-script", # Export only jni functions & classes.
	"$(location {})".format(linkscript),
	]
	native.cc_binary(
	name = name,
	copts = copts,
	linkshared = linkshared,
	linkstatic = linkstatic,
	deps = deps + [linkscript],
	linkopts = linkopts,
	)

	def tflite_cc_shared_object(
	name,
	copts = tflite_copts(),
	linkopts = [],
	linkstatic = 1,
	deps = []):
	"""Builds a shared object for TFLite."""
	tf_cc_shared_object(
	name = name,
	copts = copts,
	linkstatic = linkstatic,
	linkopts = linkopts + tflite_jni_linkopts(),
	framework_so = [],
	deps = deps,
	)

	def tf_to_tflite(name, src, options, out):
	"""Convert a frozen tensorflow graphdef to TF Lite's flatbuffer.

	Args:
	name: Name of rule.
	src: name of the input graphdef file.
	options: options passed to TOCO.
	out: name of the output flatbuffer file.
	"""

	toco_cmdline = " ".join([
	"//tensorflow/contrib/lite/toco:toco",
	"--input_format=TENSORFLOW_GRAPHDEF",
	"--output_format=TFLITE",
	("--input_file=$(location %s)" % src),
	("--output_file=$(location %s)" % out),
	] + options)
	native.genrule(
	name = name,
	srcs = [src],
	outs = [out],
	cmd = toco_cmdline,
	tools = ["//tensorflow/contrib/lite/toco:toco"],
	)

	def tflite_to_json(name, src, out):
	"""Convert a TF Lite flatbuffer to JSON.

	Args:
	name: Name of rule.
	src: name of the input flatbuffer file.
	out: name of the output JSON file.
	"""

	flatc = "@flatbuffers//:flatc"
	schema = "//tensorflow/contrib/lite/schema:schema.fbs"
	native.genrule(
	name = name,
	srcs = [schema, src],
	outs = [out],
	cmd = ("TMP=`mktemp`; cp $(location %s) $${TMP}.bin &&" +
	"$(location %s) --raw-binary --strict-json -t" +
	" -o /tmp $(location %s) -- $${TMP}.bin &&" +
	"cp $${TMP}.json $(location %s)") %
	(src, flatc, schema, out),
	tools = [flatc],
	)

	def json_to_tflite(name, src, out):
	"""Convert a JSON file to TF Lite's flatbuffer.

	Args:
	name: Name of rule.
	src: name of the input JSON file.
	out: name of the output flatbuffer file.
	"""

	flatc = "@flatbuffers//:flatc"
	schema = "//tensorflow/contrib/lite/schema:schema_fbs"
	native.genrule(
	name = name,
	srcs = [schema, src],
	outs = [out],
	cmd = ("TMP=`mktemp`; cp $(location %s) $${TMP}.json &&" +
	"$(location %s) --raw-binary --unknown-json --allow-non-utf8 -b" +
	" -o /tmp $(location %s) $${TMP}.json &&" +
	"cp $${TMP}.bin $(location %s)") %
	(src, flatc, schema, out),
	tools = [flatc],
	)

	# This is the master list of generated examples that will be made into tests. A
	# function called make_XXX_tests() must also appear in generate_examples.py.
	# Disable a test by commenting it out. If you do, add a link to a bug or issue.
	def generated_test_models():
	return [
	"add",
	"arg_min_max",
	"avg_pool",
	"batch_to_space_nd",
	"concat",
	"constant",
	"control_dep",
	"conv",
	"conv_with_shared_weights",
	"conv_to_depthwiseconv_with_shared_weights",
	"depthwiseconv",
	"div",
	"equal",
	"exp",
	"expand_dims",
	"floor",
	"floor_div",
	"fully_connected",
	"fused_batch_norm",
	"gather",
	"global_batch_norm",
	"greater",
	"greater_equal",
	"sum",
	"l2norm",
	"l2_pool",
	"less",
	"less_equal",
	"local_response_norm",
	"log_softmax",
	"log",
	"logical_and",
	"logical_or",
	"logical_xor",
	"lstm",
	"max_pool",
	"maximum",
	"mean",
	"minimum",
	"mul",
	"neg",
	"not_equal",
	"one_hot",
	"pack",
	"pad",
	"padv2",
	"prelu",
	"pow",
	"reduce_any",
	"reduce_max",
	"reduce_min",
	"reduce_prod",
	"relu",
	"relu1",
	"relu6",
	"reshape",
	"resize_bilinear",
	"rsqrt",
	"shape",
	"sigmoid",
	"sin",
	"slice",
	"softmax",
	"space_to_batch_nd",
	"space_to_depth",
	"sparse_to_dense",
	"split",
	"sqrt",
	"square",
	"squeeze",
	"strided_slice",
	"strided_slice_1d_exhaustive",
	"sub",
	"tile",
	"topk",
	"transpose",
	#"transpose_conv", # disabled due to b/111213074
	"unpack",
	"where",
	"zeros_like",
	]

	def generated_test_conversion_modes():
	"""Returns a list of conversion modes."""

	# TODO(nupurgarg): Add "pb2lite" when it's in open source. b/113614050.
	return ["toco-extended", ""]

	def generated_test_models_all():
	"""Generates a list of all tests with the different converters.

	Returns:
	List of tuples representing (conversion mode, name of test).
	"""
	conversion_modes = generated_test_conversion_modes()
	tests = generated_test_models()
	options = []
	for conversion_mode in conversion_modes:
	for test in tests:
	if conversion_mode:
	test += "_%s" % conversion_mode
	options.append((conversion_mode, test))
	return options

	def gen_zip_test(name, test_name, conversion_mode, **kwargs):
	"""Generate a zipped-example test and its dependent zip files.

	Args:
	name: str. Resulting cc_test target name
	test_name: str. Test targets this model. Comes from the list above.
	conversion_mode: str. Which conversion mode to run with. Comes from the
	list above.
	**kwargs: tf_cc_test kwargs
	"""
	toco = "//tensorflow/contrib/lite/toco:toco"
	flags = ""
	if conversion_mode:
	# TODO(nupurgarg): Comment in when pb2lite is in open source. b/113614050.
	# if conversion_mode == "pb2lite":
	# toco = "//tensorflow/contrib/lite/experimental/pb2lite:pb2lite"
	flags = "--ignore_toco_errors --run_with_extended"
	kwargs["tags"].append("skip_already_failing")
	kwargs["tags"].append("no_oss")
	kwargs["tags"].append("notap")

	gen_zipped_test_file(
	name = "zip_%s" % test_name,
	file = "%s.zip" % test_name,
	toco = toco,
	flags = flags,
	)
	tf_cc_test(name, **kwargs)

	def gen_zipped_test_file(name, file, toco, flags):
	"""Generate a zip file of tests by using :generate_examples.

	Args:
	name: str. Name of output. We will produce "`file`.files" as a target.
	file: str. The name of one of the generated_examples targets, e.g. "transpose"
	toco: str. Pathname of toco binary to run
	flags: str. Any additional flags to include
	"""
	native.genrule(
	name = file + ".files",
	cmd = (("$(locations :generate_examples) --toco $(locations {0}) " +
	" --zip_to_output {1} {2} $(@D)").format(toco, file, flags)),
	outs = [file],
	tools = [
	":generate_examples",
	toco,
	],
	)

	native.filegroup(
	name = name,
	srcs = [file],
	)

	def gen_selected_ops(name, model):
	"""Generate the library that includes only used ops.

	Args:
	name: Name of the generated library.
	model: TFLite model to interpret.
	"""
	out = name + "_registration.cc"
	tool = "//tensorflow/contrib/lite/tools:generate_op_registrations"
	tflite_path = "//tensorflow/contrib/lite"
	native.genrule(
	name = name,
	srcs = [model],
	outs = [out],
	cmd = ("$(location %s) --input_model=$(location %s) --output_registration=$(location %s) --tflite_path=%s") %
	(tool, model, out, tflite_path[2:]),
	tools = [tool],
	)