Adds new podspecs for the TensorFlow Lite iOS libraries.

PiperOrigin-RevId: 239748653

.gitignore

@@ -24,10 +24,13 @@ Pods
 Podfile.lock
 *.pbxproj
 *.xcworkspacedata
-/tensorflow/lite/tools/make/downloads/**
+/*.podspec
-/tensorflow/lite/gen/**
+/tensorflow/lite/experimental/objc/BUILD
+/tensorflow/lite/experimental/swift/BUILD
 /tensorflow/lite/examples/ios/simple/data/*.txt
 /tensorflow/lite/examples/ios/simple/data/*.tflite
+/tensorflow/lite/gen/**
+/tensorflow/lite/tools/make/downloads/**
 xcuserdata/**
 /api_init_files_list.txt
 /estimator_api_init_files_list.txt

configure.py

@@ -56,12 +56,18 @@ NCCL_LIB_PATHS = [
     'lib64/', 'lib/powerpc64le-linux-gnu/', 'lib/x86_64-linux-gnu/', ''
 ]
 
-# List of files to be configured for using Bazel on Apple platforms.
+# List of files to configure when building Bazel on Apple platforms.
 APPLE_BAZEL_FILES = [
     'tensorflow/lite/experimental/objc/BUILD',
     'tensorflow/lite/experimental/swift/BUILD'
 ]
 
+# List of files to move when building for iOS.
+IOS_FILES = [
+    'tensorflow/lite/experimental/objc/TensorFlowLiteObjC.podspec',
+    'tensorflow/lite/experimental/swift/TensorFlowLiteSwift.podspec',
+]
+
 if platform.machine() == 'ppc64le':
   _DEFAULT_TENSORRT_PATH_LINUX = '/usr/lib/powerpc64le-linux-gnu/'
 else:
@@ -1585,24 +1591,24 @@ def config_info_line(name, help_text):
   print('\t--config=%-12s\t# %s' % (name, help_text))
 
 
-def configure_apple_bazel_rules():
+def configure_ios():
-  """Configures Bazel rules for building on Apple platforms.
+  """Configures TensorFlow for iOS builds.
 
-  Enables analyzing and building Apple Bazel rules on Apple platforms. This
+  This function will only be executed if `is_macos()` is true.
-  function will only be executed if `is_macos()` is true.
   """
   if not is_macos():
     return
-  for filepath in APPLE_BAZEL_FILES:
-    print(
-        'Configuring %s file to analyze and build Bazel rules on Apple platforms.'
-        % filepath)
-    existing_filepath = os.path.join(_TF_WORKSPACE_ROOT, filepath + '.apple')
-    renamed_filepath = os.path.join(_TF_WORKSPACE_ROOT, filepath)
-    os.rename(existing_filepath, renamed_filepath)
   if _TF_CURRENT_BAZEL_VERSION is None or _TF_CURRENT_BAZEL_VERSION < 23000:
     print(
         'Building Bazel rules on Apple platforms requires Bazel 0.23 or later.')
+  for filepath in APPLE_BAZEL_FILES:
+    existing_filepath = os.path.join(_TF_WORKSPACE_ROOT, filepath + '.apple')
+    renamed_filepath = os.path.join(_TF_WORKSPACE_ROOT, filepath)
+    symlink_force(existing_filepath, renamed_filepath)
+  for filepath in IOS_FILES:
+    filename = os.path.basename(filepath)
+    new_filepath = os.path.join(_TF_WORKSPACE_ROOT, filename)
+    symlink_force(filepath, new_filepath)
 
 
 def main():
@@ -1648,7 +1654,7 @@ def main():
   if is_macos():
     environ_cp['TF_NEED_TENSORRT'] = '0'
   else:
-    environ_cp['TF_CONFIGURE_APPLE_BAZEL_RULES'] = '0'
+    environ_cp['TF_CONFIGURE_IOS'] = '0'
 
   # The numpy package on ppc64le uses OpenBLAS which has multi-threading
   # issues that lead to incorrect answers.  Set OMP_NUM_THREADS=1 at
@@ -1753,13 +1759,11 @@ def main():
 
   system_specific_config(os.environ)
 
-  if get_var(
+  if get_var(environ_cp, 'TF_CONFIGURE_IOS', 'Configure TensorFlow for iOS',
-      environ_cp, 'TF_CONFIGURE_APPLE_BAZEL_RULES',
+             False, ('Would you like to configure TensorFlow for iOS builds?'),
-      'Configure Bazel rules for Apple platforms', False,
+             'Configuring TensorFlow for iOS builds.',
-      ('Would you like to configure Bazel rules for building on Apple platforms?'
+             'Not configuring TensorFlow for iOS builds.'):
-      ), 'Configuring Bazel rules for Apple platforms.',
+    configure_ios()
-      'Not configuring Bazel rules for Apple platforms.'):
-    configure_apple_bazel_rules()
 
   print('Preconfigured Bazel build configs. You can use any of the below by '
         'adding "--config=<>" to your build command. See .bazelrc for more '

tensorflow/lite/experimental/c/BUILD

@@ -56,7 +56,7 @@ cc_library(
     srcs = ["c_api.cc"],
     hdrs = ["c_api.h"],
     copts = tflite_copts(),
-    tags = ["swift_module=TensorFlowLiteCAPI"],
+    tags = ["swift_module=TensorFlowLiteC"],
     visibility = [
         ":experimental",
     ],

tensorflow/lite/experimental/c/TensorFlowLiteC.bazel

@@ -0,0 +1,25 @@
+# Bazel rules for building the TensorFlowLiteC iOS static framework.
+#
+#   Add the build rules below to `//tensorflow/lite/experimental/c/BUILD`.
+#   Build the framework:
+#     bazel build tensorflow/lite/experimental/c:TensorFlowLiteC_framework -c opt --ios_multi_cpus=x86_64,armv7,arm64
+#   Unzip the generated framework:
+#     unzip bazel-bin/tensorflow/lite/experimental/c/TensorFlowLiteC_framework.zip -d /Users/path/to/TensorFlowLiteC.framework
+
+load("@build_bazel_rules_apple//apple:ios.bzl", "ios_static_framework")
+load("@build_bazel_rules_apple//apple:versioning.bzl", "apple_bundle_version")
+
+apple_bundle_version(
+    name = "TensorFlowLiteC_version",
+    build_version = "0.1.0",
+    short_version_string = "0.1",
+)
+
+ios_static_framework(
+    name = "TensorFlowLiteC_framework",
+    hdrs = ["c_api.h"],
+    bundle_name = "TensorFlowLiteC",
+    minimum_os_version = "9.0",
+    version = ":TensorFlowLiteC_version",
+    deps = [":c_api"],
+)

tensorflow/lite/experimental/c/TensorFlowLiteC.podspec

@@ -0,0 +1,24 @@
+# Run `pod lib lint TensorFlowLiteC.podspec` to ensure this is a valid spec.
+
+Pod::Spec.new do |s|
+  s.name             = 'TensorFlowLiteC'
+  s.version          = '0.1.0'
+  s.authors          = 'Google Inc.'
+  s.license          = { :type => 'Apache' }
+  s.homepage         = 'https://github.com/tensorflow/tensorflow'
+  s.source           = { :http => 'https://dl.google.com/dl/tensorflow/lite/frameworks/TensorFlowLiteC/0.1.0/TensorFlowLiteC-0.1.0.tar.gz' }
+  s.summary          = 'TensorFlow Lite'
+  s.description      = <<-DESC
+
+  TensorFlow Lite is TensorFlow's lightweight solution for mobile developers. It
+  enables low-latency inference of on-device machine learning models with a
+  small binary size and fast performance supporting hardware acceleration.
+                       DESC
+
+  s.ios.deployment_target = '9.0'
+
+  s.module_name = 'TensorFlowLiteC'
+  s.library = 'c++'
+  s.static_framework = true
+  s.vendored_frameworks = 'Frameworks/TensorFlowLiteC.framework'
+end

tensorflow/lite/experimental/objc/BUILD.apple

@@ -64,6 +64,7 @@ objc_library(
     srcs = SOURCES,
     hdrs = API_HEADERS,
     copts = RELEASE_COPTS,
+    module_map = "apis/module.modulemap",
     tags = DEFAULT_TAGS,
     deps = [
         "//tensorflow/lite/experimental/c:c_api",

tensorflow/lite/experimental/objc/README.md

@@ -7,6 +7,19 @@ supporting hardware acceleration.
 
 ## Getting Started
 
+To build the Objective-C TensorFlow Lite library on Apple platforms,
+[install from source](https://www.tensorflow.org/install/source#setup_for_linux_and_macos)
+or [clone the GitHub repo](https://github.com/tensorflow/tensorflow).
+Then, configure TensorFlow by navigating to the root directory and executing the
+`configure.py` script:
+
+```shell
+python configure.py
+```
+
+Follow the prompts and when asked to configure TensorFlow for iOS builds,
+enter `y`.
+
 ### Bazel
 
 In your `BUILD` file, add the `TensorFlowLite` dependency:
@@ -19,17 +32,12 @@ objc_library(
 )
 ```
 
-If you would like to build the Objective-C TensorFlow Lite library using Bazel on Apple
+In your Objective-C files, import the umbrella header:
-platforms, clone or download the [TensorFlow GitHub repo](https://github.com/tensorflow/tensorflow),
-then navigate to the root `tensorflow` directory and execute the `configure.py` script:
 
-```shell
+```objectivec
-python configure.py
+#import "TFLTensorFlowLite.h"
 ```
 
-Follow the prompts and when asked to configure the Bazel rules for Apple
-platforms, enter `y`.
-
 Build the `TensorFlowLite` Objective-C library target:
 
 ```shell
@@ -52,3 +60,26 @@ script from the root `tensorflow` directory:
 ```shell
 generate_xcodeproj.sh --genconfig tensorflow/lite/experimental/objc/TensorFlowLite.tulsiproj:TensorFlowLite --outputfolder ~/path/to/generated/TensorFlowLite.xcodeproj
 ```
+
+### CocoaPods
+
+Add the following to your `Podfile`:
+
+```ruby
+pod 'TensorFlowLiteObjC'
+```
+
+Then, run `pod install`.
+
+In your Objective-C files, import the umbrella header:
+
+```objectivec
+#import "TFLTensorFlowLite.h"
+```
+
+Or, the module if `CLANG_ENABLE_MODULES = YES` and `use_frameworks!` is
+specified in your `Podfile`:
+
+```objectivec
+@import TFLTensorFlowLite;
+```

tensorflow/lite/experimental/objc/TensorFlowLiteObjC.podspec

@@ -0,0 +1,39 @@
+# Run `pod lib lint TensorFlowLiteObjC.podspec` to ensure this is a valid spec.
+
+Pod::Spec.new do |s|
+  s.name             = 'TensorFlowLiteObjC'
+  s.version          = '0.1.0'
+  s.authors          = 'Google Inc.'
+  s.license          = { :type => 'Apache' }
+  s.homepage         = 'https://github.com/tensorflow/tensorflow'
+  s.source           = { :git => 'https://github.com/tensorflow/tensorflow.git', :tag => 'v2.0.0-alpha0' }
+  s.summary          = 'TensorFlow Lite for Objective-C'
+  s.description      = <<-DESC
+
+  TensorFlow Lite is TensorFlow's lightweight solution for Objective-C
+  developers. It enables low-latency inference of on-device machine learning
+  models with a small binary size and fast performance supporting hardware
+  acceleration.
+                       DESC
+
+  s.ios.deployment_target = '9.0'
+
+  s.module_name = 'TFLTensorFlowLite'
+  s.static_framework = true
+  s.prefix_header_file = false
+
+  base_dir = 'tensorflow/lite/experimental/objc/'
+  s.public_header_files = base_dir + 'apis/*.h'
+  s.source_files = base_dir + '{apis,sources}/*.{h,m,mm}'
+  s.module_map = base_dir + 'apis/framework.modulemap'
+  s.dependency 'TensorFlowLiteC', "#{s.version}"
+  s.pod_target_xcconfig = {
+    'HEADER_SEARCH_PATHS' =>
+      '"${PODS_TARGET_SRCROOT}" ' +
+      '"${PODS_TARGET_SRCROOT}/"' + base_dir  + '"apis"',
+  }
+
+  s.test_spec 'Tests' do |ts|
+    ts.source_files = base_dir + 'tests/*.m'
+  end
+end

tensorflow/lite/experimental/objc/apis/TFLTensorFlowLite.h

@@ -0,0 +1,18 @@
+// Copyright 2019 Google Inc. All rights reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at:
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#import "TFLInterpreter.h"
+#import "TFLInterpreterOptions.h"
+#import "TFLQuantizationParameters.h"
+#import "TFLTensor.h"

tensorflow/lite/experimental/objc/apis/framework.modulemap

@@ -0,0 +1,10 @@
+framework module TFLTensorFlowLite {
+    umbrella header "TFLTensorFlowLite.h"
+
+    header "TFLInterpreter.h"
+    header "TFLInterpreterOptions.h"
+    header "TFLQuantizationParameters.h"
+    header "TFLTensor.h"
+
+    export *
+}

tensorflow/lite/experimental/objc/apis/module.modulemap

@@ -0,0 +1,10 @@
+module TFLTensorFlowLite {
+    umbrella header "TFLTensorFlowLite.h"
+
+    header "TFLInterpreter.h"
+    header "TFLInterpreterOptions.h"
+    header "TFLQuantizationParameters.h"
+    header "TFLTensor.h"
+
+    export *
+}

tensorflow/lite/experimental/swift/BUILD.apple

@@ -4,8 +4,6 @@ package(default_visibility = ["//visibility:private"])
 
 licenses(["notice"])  # Apache 2.0
 
-exports_files(["LICENSE"])
-
 load("@build_bazel_rules_apple//apple:ios.bzl", "ios_application", "ios_unit_test")
 load("@build_bazel_rules_swift//swift:swift.bzl", "swift_library")
 

tensorflow/lite/experimental/swift/LICENSE

@@ -1,202 +0,0 @@
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tensorflow/lite/experimental/swift/README.md

@@ -7,6 +7,19 @@ hardware acceleration.
 
 ## Getting Started
 
+To build the Swift TensorFlow Lite library on Apple platforms,
+[install from source](https://www.tensorflow.org/install/source#setup_for_linux_and_macos)
+or [clone the GitHub repo](https://github.com/tensorflow/tensorflow).
+Then, configure TensorFlow by navigating to the root directory and executing the
+`configure.py` script:
+
+```shell
+python configure.py
+```
+
+Follow the prompts and when asked to configure TensorFlow for iOS builds,
+enter `y`.
+
 ### Bazel
 
 In your `BUILD` file, add the `TensorFlowLite` dependency:
@@ -25,17 +38,6 @@ In your Swift files, import the module:
 import TensorFlowLite
 ```
 
-If you would like to build the Swift TensorFlow Lite library using Bazel on Apple
-platforms, clone or download the [TensorFlow GitHub repo](https://github.com/tensorflow/tensorflow),
-then navigate to the root `tensorflow` directory and execute the `configure.py` script:
-
-```shell
-python configure.py
-```
-
-Follow the prompts and when asked to configure the Bazel rules for Apple
-platforms, enter `y`.
-
 Build the `TensorFlowLite` Swift library target:
 
 ```shell
@@ -61,3 +63,19 @@ script from the root `tensorflow` directory:
 ```shell
 generate_xcodeproj.sh --genconfig tensorflow/lite/experimental/swift/TensorFlowLite.tulsiproj:TensorFlowLite --outputfolder ~/path/to/generated/TensorFlowLite.xcodeproj
 ```
+
+### CocoaPods
+
+Add the following to your `Podfile`:
+
+```ruby
+pod 'TensorFlowLiteSwift'
+```
+
+Then, run `pod install`.
+
+In your Swift files, import the module:
+
+```swift
+import TensorFlowLite
+```

tensorflow/lite/experimental/swift/Sources/Interpreter.swift

@@ -13,7 +13,7 @@
 // limitations under the License.
 
 import Foundation
-import TensorFlowLiteCAPI
+import TensorFlowLiteC
 
 /// A TensorFlow Lite interpreter that performs inference from a given model.
 public final class Interpreter {

tensorflow/lite/experimental/swift/Sources/Model.swift

@@ -13,7 +13,7 @@
 // limitations under the License.
 
 import Foundation
-import TensorFlowLiteCAPI
+import TensorFlowLiteC
 
 /// A TensorFlow Lite model used by the 'Interpreter` to perform inference.
 final class Model {

tensorflow/lite/experimental/swift/Sources/Tensor.swift

@@ -13,7 +13,7 @@
 // limitations under the License.
 
 import Foundation
-import TensorFlowLiteCAPI
+import TensorFlowLiteC
 
 /// An input or output tensor in a TensorFlow Lite graph.
 public struct Tensor {

tensorflow/lite/experimental/swift/TensorFlowLiteSwift.podspec

@@ -0,0 +1,31 @@
+# Run `pod lib lint TensorFlowLiteSwift.podspec` to ensure this is a valid spec.
+
+Pod::Spec.new do |s|
+  s.name             = 'TensorFlowLiteSwift'
+  s.version          = '0.1.0'
+  s.authors          = 'Google Inc.'
+  s.license          = { :type => 'Apache' }
+  s.homepage         = 'https://github.com/tensorflow/tensorflow'
+  s.source           = { :git => 'https://github.com/tensorflow/tensorflow.git', :tag => 'v2.0.0-alpha0' }
+  s.summary          = 'TensorFlow Lite for Swift'
+  s.description      = <<-DESC
+
+  TensorFlow Lite is TensorFlow's lightweight solution for Swift developers. It
+  enables low-latency inference of on-device machine learning models with a
+  small binary size and fast performance supporting hardware acceleration.
+                       DESC
+
+  s.ios.deployment_target = '9.0'
+  s.swift_version = '4.2'
+
+  s.module_name = 'TensorFlowLite'
+  s.static_framework = true
+
+  base_dir = 'tensorflow/lite/experimental/swift/'
+  s.source_files = base_dir + 'Sources/*.swift'
+  s.dependency 'TensorFlowLiteC', "#{s.version}"
+
+  s.test_spec 'Tests' do |ts|
+    ts.source_files = base_dir + 'Tests/*.swift'
+  end
+end