From 57e0d1acc21507e347953d0c2deceb99cdbd0b33 Mon Sep 17 00:00:00 2001 From: Frank Chen Date: Wed, 24 Jul 2019 18:43:43 -0700 Subject: [PATCH] Mechanical replacement of download.tensorflow.org with https equivalent. PiperOrigin-RevId: 259862509 --- WORKSPACE | 10 +-- .../mlir/tensorflow/ir/control_flow_ops.h | 12 +-- .../mlir/tensorflow/ir/tf_executor_ops.td | 14 ++-- .../nmt_with_attention.ipynb | 2 +- .../eval/python/classifier_metrics_impl.py | 4 +- .../contrib/makefile/download_dependencies.sh | 2 +- tensorflow/examples/android/README.md | 6 +- .../generate_streaming_test_wav.py | 2 +- tensorflow/examples/speech_commands/train.py | 2 +- .../lite/examples/ios/download_models.sh | 4 +- tensorflow/lite/examples/python/README.md | 2 +- tensorflow/lite/g3doc/guide/hosted_models.md | 80 +++++++++---------- .../lite/g3doc/models/smart_reply/overview.md | 2 +- .../lite/g3doc/performance/benchmarks.md | 8 +- tensorflow/lite/java/demo/app/build.gradle | 4 +- .../lite/models/smartreply/g3doc/README.md | 4 +- tensorflow/lite/tools/benchmark/ios/README.md | 2 +- tensorflow/tools/graph_transforms/README.md | 4 +- tensorflow/workspace.bzl | 8 +- 19 files changed, 87 insertions(+), 85 deletions(-) diff --git a/WORKSPACE b/WORKSPACE index d2c65bc1b1d..86830a09476 100644 --- a/WORKSPACE +++ b/WORKSPACE @@ -105,7 +105,7 @@ http_archive( sha256 = "7efe12a8363f09bc24d7b7a450304a15655a57a7751929b2c1593a71183bb105", urls = [ "http://storage.googleapis.com/download.tensorflow.org/models/inception_v1.zip", - "http://download.tensorflow.org/models/inception_v1.zip", + "https://storage.googleapis.com/download.tensorflow.org/models/inception_v1.zip", ], ) @@ -115,7 +115,7 @@ http_archive( sha256 = "bddd81ea5c80a97adfac1c9f770e6f55cbafd7cce4d3bbe15fbeb041e6b8f3e8", urls = [ "http://storage.googleapis.com/download.tensorflow.org/models/object_detection/ssd_mobilenet_v1_android_export.zip", - "http://download.tensorflow.org/models/object_detection/ssd_mobilenet_v1_android_export.zip", + "https://storage.googleapis.com/download.tensorflow.org/models/object_detection/ssd_mobilenet_v1_android_export.zip", ], ) @@ -125,7 +125,7 @@ http_archive( sha256 = "859edcddf84dddb974c36c36cfc1f74555148e9c9213dedacf1d6b613ad52b96", urls = [ "http://storage.googleapis.com/download.tensorflow.org/models/mobile_multibox_v1a.zip", - "http://download.tensorflow.org/models/mobile_multibox_v1a.zip", + "https://storage.googleapis.com/download.tensorflow.org/models/mobile_multibox_v1a.zip", ], ) @@ -135,7 +135,7 @@ http_archive( sha256 = "3d374a730aef330424a356a8d4f04d8a54277c425e274ecb7d9c83aa912c6bfa", urls = [ "http://storage.googleapis.com/download.tensorflow.org/models/stylize_v1.zip", - "http://download.tensorflow.org/models/stylize_v1.zip", + "https://storage.googleapis.com/download.tensorflow.org/models/stylize_v1.zip", ], ) @@ -145,6 +145,6 @@ http_archive( sha256 = "c3ec4fea3158eb111f1d932336351edfe8bd515bb6e87aad4f25dbad0a600d0c", urls = [ "http://storage.googleapis.com/download.tensorflow.org/models/speech_commands_v0.01.zip", - "http://download.tensorflow.org/models/speech_commands_v0.01.zip", + "https://storage.googleapis.com/download.tensorflow.org/models/speech_commands_v0.01.zip", ], ) diff --git a/tensorflow/compiler/mlir/tensorflow/ir/control_flow_ops.h b/tensorflow/compiler/mlir/tensorflow/ir/control_flow_ops.h index 2756b4c0885..4bf7029421e 100644 --- a/tensorflow/compiler/mlir/tensorflow/ir/control_flow_ops.h +++ b/tensorflow/compiler/mlir/tensorflow/ir/control_flow_ops.h @@ -65,7 +65,7 @@ class TFControlType : public Type::TypeBase { // tensor needs its own _tf.Enter to be made available inside the while loop. // // More details can be found in Tensorflow Controlflow white paper: -// http://download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf +// https://storage.googleapis.com/download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf // // This is defined in Tensorflow as: // @@ -100,7 +100,7 @@ class EnterOp // of the operand type along with the index of the first match encountered. // // More details can be found in Tensorflow Controlflow white paper: -// http://download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf +// https://storage.googleapis.com/download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf // // This is defined in TensorFlow as: // @@ -130,7 +130,7 @@ class MergeOp : public Op::Impl, // outside of loop. Each returned tensor needs its own _tf.Exit. // // More details can be found in Tensorflow Controlflow white paper: -// http://download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf +// https://storage.googleapis.com/download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf // // This is defined in Tensorflow as: // diff --git a/tensorflow/compiler/mlir/tensorflow/ir/tf_executor_ops.td b/tensorflow/compiler/mlir/tensorflow/ir/tf_executor_ops.td index 748416a8142..d8b92468cd0 100644 --- a/tensorflow/compiler/mlir/tensorflow/ir/tf_executor_ops.td +++ b/tensorflow/compiler/mlir/tensorflow/ir/tf_executor_ops.td @@ -221,7 +221,7 @@ def TfExecutor_SwitchOp : TfExecutor_Op<"Switch", let description = [{ More details can be found in Tensorflow Control Flow white paper: - http://download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf + https://storage.googleapis.com/download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf This is defined in TensorFlow as: @@ -302,7 +302,7 @@ def TfExecutor_MergeOp : TfExecutor_Op<"Merge", [NoSideEffect, ControlOperandsAf let description = [{ More details can be found in Tensorflow Control Flow white paper: - http://download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf + https://storage.googleapis.com/download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf This is defined in TensorFlow as: @@ -339,7 +339,7 @@ def TfExecutor_EnterOp : TfExecutor_Op<"Enter", let description = [{ More details can be found in Tensorflow Control Flow white paper: - http://download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf + https://storage.googleapis.com/download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf Each tensor needs its own tf_executor.Enter to be made available inside a while loop. @@ -390,7 +390,7 @@ def TfExecutor_NextIterationSourceOp : TfExecutor_Op<"NextIteration.Source", [No of a while loop. Each loop variable needs its own NextIteration op. More details can be found in Tensorflow Control Flow white paper: - http://download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf + https://storage.googleapis.com/download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf In the TF executor dialect, the NextIteration op is broken into tf_executor.NextIteration.sink and tf_executor.NextIteration.source because @@ -447,7 +447,7 @@ def TfExecutor_NextIterationSinkOp : TfExecutor_Op<"NextIteration.Sink"> { of a while loop. Each loop variable needs its own NextIteration op. More details can be found in Tensorflow Control Flow white paper: - http://download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf + https://storage.googleapis.com/download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf In the TF executor dialect, the NextIteration op is broken into tf_executor.NextIteration.sink and tf_executor.NextIteration.source because @@ -507,7 +507,7 @@ def TfExecutor_ExitOp : TfExecutor_Op<"Exit", let description = [{ More details can be found in Tensorflow Control Flow white paper: - http://download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf + https://storage.googleapis.com/download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf This is defined in Tensorflow as: @@ -579,7 +579,7 @@ def TfExecutor_LoopCondOp : TfExecutor_Op<"LoopCond", [NoSideEffect]> { let description = [{ More details can be found in Tensorflow Control Flow white paper: - http://download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf + https://storage.googleapis.com/download.tensorflow.org/paper/white_paper_tf_control_flow_implementation_2017_11_1.pdf This is defined in Tensorflow as: diff --git a/tensorflow/contrib/eager/python/examples/nmt_with_attention/nmt_with_attention.ipynb b/tensorflow/contrib/eager/python/examples/nmt_with_attention/nmt_with_attention.ipynb index 512605a17eb..cabc71c98e1 100644 --- a/tensorflow/contrib/eager/python/examples/nmt_with_attention/nmt_with_attention.ipynb +++ b/tensorflow/contrib/eager/python/examples/nmt_with_attention/nmt_with_attention.ipynb @@ -117,7 +117,7 @@ "source": [ "# Download the file\n", "path_to_zip = tf.keras.utils.get_file(\n", - " 'spa-eng.zip', origin='http://download.tensorflow.org/data/spa-eng.zip', \n", + " 'spa-eng.zip', origin='https://storage.googleapis.com/download.tensorflow.org/data/spa-eng.zip', \n", " extract=True)\n", "\n", "path_to_file = os.path.dirname(path_to_zip)+\"/spa-eng/spa.txt\"" diff --git a/tensorflow/contrib/gan/python/eval/python/classifier_metrics_impl.py b/tensorflow/contrib/gan/python/eval/python/classifier_metrics_impl.py index 2c301267900..43e1c69bf73 100644 --- a/tensorflow/contrib/gan/python/eval/python/classifier_metrics_impl.py +++ b/tensorflow/contrib/gan/python/eval/python/classifier_metrics_impl.py @@ -74,7 +74,7 @@ __all__ = [ 'INCEPTION_DEFAULT_IMAGE_SIZE', ] -INCEPTION_URL = 'http://download.tensorflow.org/models/frozen_inception_v1_2015_12_05.tar.gz' +INCEPTION_URL = 'https://storage.googleapis.com/download.tensorflow.org/models/frozen_inception_v1_2015_12_05.tar.gz' INCEPTION_FROZEN_GRAPH = 'inceptionv1_for_inception_score.pb' INCEPTION_INPUT = 'Mul:0' INCEPTION_OUTPUT = 'logits:0' @@ -123,7 +123,7 @@ def preprocess_image(images, """Prepare a batch of images for evaluation. This is the preprocessing portion of the graph from - http://download.tensorflow.org/models/image/imagenet/inception-2015-12-05.tgz. + https://storage.googleapis.com/download.tensorflow.org/models/image/imagenet/inception-2015-12-05.tgz. Note that it expects Tensors in [0, 255]. This function maps pixel values to [-1, 1] and resizes to match the InceptionV1 network. diff --git a/tensorflow/contrib/makefile/download_dependencies.sh b/tensorflow/contrib/makefile/download_dependencies.sh index efa122b34d8..6cf1145021c 100755 --- a/tensorflow/contrib/makefile/download_dependencies.sh +++ b/tensorflow/contrib/makefile/download_dependencies.sh @@ -140,7 +140,7 @@ replace_by_sed 's#static uint32x2_t p2ui_CONJ_XOR = vld1_u32( conj_XOR_DATA );#s replace_by_sed 's#static uint64x2_t p2ul_CONJ_XOR = vld1q_u64( p2ul_conj_XOR_DATA );#static uint64x2_t p2ul_CONJ_XOR;// = vld1q_u64( p2ul_conj_XOR_DATA ); - Removed by script#' \ "${DOWNLOADS_DIR}/eigen/Eigen/src/Core/arch/NEON/Complex.h" # TODO(satok): Remove this once protobuf/autogen.sh is fixed. -replace_by_sed 's#https://googlemock.googlecode.com/files/gmock-1.7.0.zip#http://download.tensorflow.org/deps/gmock-1.7.0.zip#' \ +replace_by_sed 's#https://googlemock.googlecode.com/files/gmock-1.7.0.zip#https://storage.googleapis.com/download.tensorflow.org/deps/gmock-1.7.0.zip#' \ "${DOWNLOADS_DIR}/protobuf/autogen.sh" cat "third_party/eigen3/gebp_neon.patch" | patch "${DOWNLOADS_DIR}/eigen/Eigen/src/Core/products/GeneralBlockPanelKernel.h" diff --git a/tensorflow/examples/android/README.md b/tensorflow/examples/android/README.md index 4e4e1685f6d..bb646d2da0e 100644 --- a/tensorflow/examples/android/README.md +++ b/tensorflow/examples/android/README.md @@ -45,7 +45,7 @@ on API >= 14 devices. ## Prebuilt Components: -The fastest path to trying the demo is to download the [prebuilt demo APK](http://download.tensorflow.org/deps/tflite/TfLiteCameraDemo.apk). +The fastest path to trying the demo is to download the [prebuilt demo APK](https://storage.googleapis.com/download.tensorflow.org/deps/tflite/TfLiteCameraDemo.apk). Also available are precompiled native libraries, and a jcenter package that you may simply drop into your own applications. See @@ -109,7 +109,9 @@ protobuf compilation. NOTE: Bazel does not currently support building for Android on Windows. Full support for gradle/cmake builds is coming soon, but in the meantime we suggest -that Windows users download the [prebuilt demo APK](http://download.tensorflow.org/deps/tflite/TfLiteCameraDemo.apk) instead. +that Windows users download the +[prebuilt demo APK](https://storage.googleapis.com/download.tensorflow.org/deps/tflite/TfLiteCameraDemo.apk) +instead. ##### Install Bazel and Android Prerequisites diff --git a/tensorflow/examples/speech_commands/generate_streaming_test_wav.py b/tensorflow/examples/speech_commands/generate_streaming_test_wav.py index 98589069277..d3df7f4613e 100644 --- a/tensorflow/examples/speech_commands/generate_streaming_test_wav.py +++ b/tensorflow/examples/speech_commands/generate_streaming_test_wav.py @@ -174,7 +174,7 @@ if __name__ == '__main__': '--data_url', type=str, # pylint: disable=line-too-long - default='http://download.tensorflow.org/data/speech_commands_v0.01.tar.gz', + default='https://storage.googleapis.com/download.tensorflow.org/data/speech_commands_v0.01.tar.gz', # pylint: enable=line-too-long help='Location of speech training data') parser.add_argument( diff --git a/tensorflow/examples/speech_commands/train.py b/tensorflow/examples/speech_commands/train.py index 43a399b912e..3686b7dd2b2 100644 --- a/tensorflow/examples/speech_commands/train.py +++ b/tensorflow/examples/speech_commands/train.py @@ -301,7 +301,7 @@ if __name__ == '__main__': '--data_url', type=str, # pylint: disable=line-too-long - default='http://download.tensorflow.org/data/speech_commands_v0.02.tar.gz', + default='https://storage.googleapis.com/download.tensorflow.org/data/speech_commands_v0.02.tar.gz', # pylint: enable=line-too-long help='Location of speech training data archive on the web.') parser.add_argument( diff --git a/tensorflow/lite/examples/ios/download_models.sh b/tensorflow/lite/examples/ios/download_models.sh index a450aba042e..68a9c96b84e 100755 --- a/tensorflow/lite/examples/ios/download_models.sh +++ b/tensorflow/lite/examples/ios/download_models.sh @@ -17,8 +17,8 @@ set -ex SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" -FLOAT_MODEL_URL="http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_224.tgz" -QUANTIZED_MODEL_URL="http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz" +FLOAT_MODEL_URL="https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_224.tgz" +QUANTIZED_MODEL_URL="https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz" DOWNLOADS_DIR=$(mktemp -d) cd "$SCRIPT_DIR" diff --git a/tensorflow/lite/examples/python/README.md b/tensorflow/lite/examples/python/README.md index b5ad7d1a412..ddfedb2916c 100644 --- a/tensorflow/lite/examples/python/README.md +++ b/tensorflow/lite/examples/python/README.md @@ -18,7 +18,7 @@ a good demonstration of a model trained to recognize 1,000 different objects. # Get photo curl https://raw.githubusercontent.com/tensorflow/tensorflow/master/tensorflow/lite/examples/label_image/testdata/grace_hopper.bmp > /tmp/grace_hopper.bmp # Get model -curl http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_224.tgz | tar xzv -C /tmp +curl https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_224.tgz | tar xzv -C /tmp # Get labels curl https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_1.0_224_frozen.tgz | tar xzv -C /tmp mobilenet_v1_1.0_224/labels.txt diff --git a/tensorflow/lite/g3doc/guide/hosted_models.md b/tensorflow/lite/g3doc/guide/hosted_models.md index 323d31ba897..ba26ff80065 100644 --- a/tensorflow/lite/g3doc/guide/hosted_models.md +++ b/tensorflow/lite/g3doc/guide/hosted_models.md @@ -21,29 +21,29 @@ For more information about image classification, see classification models offer the smallest model size and fastest performance, at the expense of accuracy. -Model name | Paper and model | Model size | Top-1 accuracy | Top-5 accuracy | TF Lite performance ---------------------------- | :-------------------------------------------------------------------------------------------------------------------------------------------------------: | ---------: | -------------: | -------------: | ------------------: -Mobilenet_V1_0.25_128_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.25_128_quant.tgz) | 0.5 Mb | 39.5% | 64.4% | 3.7 ms -Mobilenet_V1_0.25_160_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.25_160_quant.tgz) | 0.5 Mb | 42.8% | 68.1% | 5.5 ms -Mobilenet_V1_0.25_192_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.25_192_quant.tgz) | 0.5 Mb | 45.7% | 70.8% | 7.9 ms -Mobilenet_V1_0.25_224_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.25_224_quant.tgz) | 0.5 Mb | 48.2% | 72.8% | 10.4 ms -Mobilenet_V1_0.50_128_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.5_128_quant.tgz) | 1.4 Mb | 54.9% | 78.1% | 8.8 ms -Mobilenet_V1_0.50_160_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.5_160_quant.tgz) | 1.4 Mb | 57.2% | 80.5% | 13.0 ms -Mobilenet_V1_0.50_192_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.5_192_quant.tgz) | 1.4 Mb | 59.9% | 82.1% | 18.3 ms -Mobilenet_V1_0.50_224_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.5_224_quant.tgz) | 1.4 Mb | 61.2% | 83.2% | 24.7 ms -Mobilenet_V1_0.75_128_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.75_128_quant.tgz) | 2.6 Mb | 55.9% | 79.1% | 16.2 ms -Mobilenet_V1_0.75_160_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.75_160_quant.tgz) | 2.6 Mb | 62.4% | 83.7% | 24.3 ms -Mobilenet_V1_0.75_192_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.75_192_quant.tgz) | 2.6 Mb | 66.1% | 86.2% | 33.8 ms -Mobilenet_V1_0.75_224_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.75_224_quant.tgz) | 2.6 Mb | 66.9% | 86.9% | 45.4 ms -Mobilenet_V1_1.0_128_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_128_quant.tgz) | 4.3 Mb | 63.3% | 84.1% | 24.9 ms -Mobilenet_V1_1.0_160_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_160_quant.tgz) | 4.3 Mb | 66.9% | 86.7% | 37.4 ms -Mobilenet_V1_1.0_192_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_192_quant.tgz) | 4.3 Mb | 69.1% | 88.1% | 51.9 ms -Mobilenet_V1_1.0_224_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz) | 4.3 Mb | 70.0% | 89.0% | 70.2 ms -Mobilenet_V2_1.0_224_quant | [paper](https://arxiv.org/abs/1806.08342), [tflite&pb](http://download.tensorflow.org/models/tflite_11_05_08/mobilenet_v2_1.0_224_quant.tgz) | 3.4 Mb | 70.8% | 89.9% | 53.4 ms -Inception_V1_quant | [paper](https://arxiv.org/abs/1409.4842), [tflite&pb](http://download.tensorflow.org/models/inception_v1_224_quant_20181026.tgz) | 6.4 Mb | 70.1% | 89.8% | 154.5 ms -Inception_V2_quant | [paper](https://arxiv.org/abs/1512.00567), [tflite&pb](http://download.tensorflow.org/models/inception_v2_224_quant_20181026.tgz) | 11 Mb | 73.5% | 91.4% | 235.0 ms -Inception_V3_quant | [paper](https://arxiv.org/abs/1806.08342),[tflite&pb](http://download.tensorflow.org/models/tflite_11_05_08/inception_v3_quant.tgz) | 23 Mb | 77.5% | 93.7% | 637 ms -Inception_V4_quant | [paper](https://arxiv.org/abs/1602.07261), [tflite&pb](http://download.tensorflow.org/models/inception_v4_299_quant_20181026.tgz) | 41 Mb | 79.5% | 93.9% | 1250.8 ms +Model name | Paper and model | Model size | Top-1 accuracy | Top-5 accuracy | TF Lite performance +--------------------------- | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | ---------: | -------------: | -------------: | ------------------: +Mobilenet_V1_0.25_128_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.25_128_quant.tgz) | 0.5 Mb | 39.5% | 64.4% | 3.7 ms +Mobilenet_V1_0.25_160_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.25_160_quant.tgz) | 0.5 Mb | 42.8% | 68.1% | 5.5 ms +Mobilenet_V1_0.25_192_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.25_192_quant.tgz) | 0.5 Mb | 45.7% | 70.8% | 7.9 ms +Mobilenet_V1_0.25_224_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.25_224_quant.tgz) | 0.5 Mb | 48.2% | 72.8% | 10.4 ms +Mobilenet_V1_0.50_128_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.5_128_quant.tgz) | 1.4 Mb | 54.9% | 78.1% | 8.8 ms +Mobilenet_V1_0.50_160_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.5_160_quant.tgz) | 1.4 Mb | 57.2% | 80.5% | 13.0 ms +Mobilenet_V1_0.50_192_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.5_192_quant.tgz) | 1.4 Mb | 59.9% | 82.1% | 18.3 ms +Mobilenet_V1_0.50_224_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.5_224_quant.tgz) | 1.4 Mb | 61.2% | 83.2% | 24.7 ms +Mobilenet_V1_0.75_128_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.75_128_quant.tgz) | 2.6 Mb | 55.9% | 79.1% | 16.2 ms +Mobilenet_V1_0.75_160_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.75_160_quant.tgz) | 2.6 Mb | 62.4% | 83.7% | 24.3 ms +Mobilenet_V1_0.75_192_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.75_192_quant.tgz) | 2.6 Mb | 66.1% | 86.2% | 33.8 ms +Mobilenet_V1_0.75_224_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_0.75_224_quant.tgz) | 2.6 Mb | 66.9% | 86.9% | 45.4 ms +Mobilenet_V1_1.0_128_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_128_quant.tgz) | 4.3 Mb | 63.3% | 84.1% | 24.9 ms +Mobilenet_V1_1.0_160_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_160_quant.tgz) | 4.3 Mb | 66.9% | 86.7% | 37.4 ms +Mobilenet_V1_1.0_192_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_192_quant.tgz) | 4.3 Mb | 69.1% | 88.1% | 51.9 ms +Mobilenet_V1_1.0_224_quant | [paper](https://arxiv.org/pdf/1712.05877.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz) | 4.3 Mb | 70.0% | 89.0% | 70.2 ms +Mobilenet_V2_1.0_224_quant | [paper](https://arxiv.org/abs/1806.08342), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/tflite_11_05_08/mobilenet_v2_1.0_224_quant.tgz) | 3.4 Mb | 70.8% | 89.9% | 53.4 ms +Inception_V1_quant | [paper](https://arxiv.org/abs/1409.4842), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/inception_v1_224_quant_20181026.tgz) | 6.4 Mb | 70.1% | 89.8% | 154.5 ms +Inception_V2_quant | [paper](https://arxiv.org/abs/1512.00567), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/inception_v2_224_quant_20181026.tgz) | 11 Mb | 73.5% | 91.4% | 235.0 ms +Inception_V3_quant | [paper](https://arxiv.org/abs/1806.08342),[tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/tflite_11_05_08/inception_v3_quant.tgz) | 23 Mb | 77.5% | 93.7% | 637 ms +Inception_V4_quant | [paper](https://arxiv.org/abs/1602.07261), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/inception_v4_299_quant_20181026.tgz) | 41 Mb | 79.5% | 93.9% | 1250.8 ms Note: The model files include both TF Lite FlatBuffer and Tensorflow frozen Graph. @@ -68,23 +68,23 @@ ResNet_V2_101 | [paper](https://arxiv.org/abs/1603.05027), [tflite&pb](h Inception_V3 | [paper](http://arxiv.org/abs/1512.00567), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/inception_v3_2018_04_27.tgz) | 95.3 Mb | 77.9% | 93.8% | 1433 ms | 1522 ms Inception_V4 | [paper](http://arxiv.org/abs/1602.07261), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/inception_v4_2018_04_27.tgz) | 170.7 Mb | 80.1% | 95.1% | 2986 ms | 3139 ms Inception_ResNet_V2 | [paper](https://arxiv.org/abs/1602.07261), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/tflite/model_zoo/upload_20180427/inception_resnet_v2_2018_04_27.tgz) | 121.0 Mb | 77.5% | 94.0% | 2731 ms | 2926 ms -Mobilenet_V1_0.25_128 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.25_128.tgz) | 1.9 Mb | 41.4% | 66.2% | 6.2 ms | 13.0 ms -Mobilenet_V1_0.25_160 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.25_160.tgz) | 1.9 Mb | 45.4% | 70.2% | 8.6 ms | 19.5 ms -Mobilenet_V1_0.25_192 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.25_192.tgz) | 1.9 Mb | 47.1% | 72.0% | 12.1 ms | 27.8 ms -Mobilenet_V1_0.25_224 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.25_224.tgz) | 1.9 Mb | 49.7% | 74.1% | 16.2 ms | 37.3 ms -Mobilenet_V1_0.50_128 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.5_128.tgz) | 5.3 Mb | 56.2% | 79.3% | 18.1 ms | 29.9 ms -Mobilenet_V1_0.50_160 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.5_160.tgz) | 5.3 Mb | 59.0% | 81.8% | 26.8 ms | 45.9 ms -Mobilenet_V1_0.50_192 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.5_192.tgz) | 5.3 Mb | 61.7% | 83.5% | 35.6 ms | 65.3 ms -Mobilenet_V1_0.50_224 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.5_224.tgz) | 5.3 Mb | 63.2% | 84.9% | 47.6 ms | 164.2 ms -Mobilenet_V1_0.75_128 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.75_128.tgz) | 10.3 Mb | 62.0% | 83.8% | 34.6 ms | 48.7 ms -Mobilenet_V1_0.75_160 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.75_160.tgz) | 10.3 Mb | 65.2% | 85.9% | 51.3 ms | 75.2 ms -Mobilenet_V1_0.75_192 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.75_192.tgz) | 10.3 Mb | 67.1% | 87.2% | 71.7 ms | 107.0 ms -Mobilenet_V1_0.75_224 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.75_224.tgz) | 10.3 Mb | 68.3% | 88.1% | 95.7 ms | 143.4 ms -Mobilenet_V1_1.0_128 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_128.tgz) | 16.9 Mb | 65.2% | 85.7% | 57.4 ms | 76.8 ms -Mobilenet_V1_1.0_160 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_160.tgz) | 16.9 Mb | 68.0% | 87.7% | 86.0 ms | 117.7 ms -Mobilenet_V1_1.0_192 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_192.tgz) | 16.9 Mb | 69.9% | 89.1% | 118.6 ms | 167.3 ms -Mobilenet_V1_1.0_224 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_224.tgz) | 16.9 Mb | 71.0% | 89.9% | 160.1 ms | 224.3 ms -Mobilenet_V2_1.0_224 | [paper](https://arxiv.org/pdf/1801.04381.pdf), [tflite&pb](http://download.tensorflow.org/models/tflite_11_05_08/mobilenet_v2_1.0_224.tgz) | 14.0 Mb | 71.8% | 90.6% | 117 ms | +Mobilenet_V1_0.25_128 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.25_128.tgz) | 1.9 Mb | 41.4% | 66.2% | 6.2 ms | 13.0 ms +Mobilenet_V1_0.25_160 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.25_160.tgz) | 1.9 Mb | 45.4% | 70.2% | 8.6 ms | 19.5 ms +Mobilenet_V1_0.25_192 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.25_192.tgz) | 1.9 Mb | 47.1% | 72.0% | 12.1 ms | 27.8 ms +Mobilenet_V1_0.25_224 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.25_224.tgz) | 1.9 Mb | 49.7% | 74.1% | 16.2 ms | 37.3 ms +Mobilenet_V1_0.50_128 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.5_128.tgz) | 5.3 Mb | 56.2% | 79.3% | 18.1 ms | 29.9 ms +Mobilenet_V1_0.50_160 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.5_160.tgz) | 5.3 Mb | 59.0% | 81.8% | 26.8 ms | 45.9 ms +Mobilenet_V1_0.50_192 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.5_192.tgz) | 5.3 Mb | 61.7% | 83.5% | 35.6 ms | 65.3 ms +Mobilenet_V1_0.50_224 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.5_224.tgz) | 5.3 Mb | 63.2% | 84.9% | 47.6 ms | 164.2 ms +Mobilenet_V1_0.75_128 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.75_128.tgz) | 10.3 Mb | 62.0% | 83.8% | 34.6 ms | 48.7 ms +Mobilenet_V1_0.75_160 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.75_160.tgz) | 10.3 Mb | 65.2% | 85.9% | 51.3 ms | 75.2 ms +Mobilenet_V1_0.75_192 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.75_192.tgz) | 10.3 Mb | 67.1% | 87.2% | 71.7 ms | 107.0 ms +Mobilenet_V1_0.75_224 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_0.75_224.tgz) | 10.3 Mb | 68.3% | 88.1% | 95.7 ms | 143.4 ms +Mobilenet_V1_1.0_128 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_128.tgz) | 16.9 Mb | 65.2% | 85.7% | 57.4 ms | 76.8 ms +Mobilenet_V1_1.0_160 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_160.tgz) | 16.9 Mb | 68.0% | 87.7% | 86.0 ms | 117.7 ms +Mobilenet_V1_1.0_192 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_192.tgz) | 16.9 Mb | 69.9% | 89.1% | 118.6 ms | 167.3 ms +Mobilenet_V1_1.0_224 | [paper](https://arxiv.org/pdf/1704.04861.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_224.tgz) | 16.9 Mb | 71.0% | 89.9% | 160.1 ms | 224.3 ms +Mobilenet_V2_1.0_224 | [paper](https://arxiv.org/pdf/1801.04381.pdf), [tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/tflite_11_05_08/mobilenet_v2_1.0_224.tgz) | 14.0 Mb | 71.8% | 90.6% | 117 ms | ### AutoML mobile models diff --git a/tensorflow/lite/g3doc/models/smart_reply/overview.md b/tensorflow/lite/g3doc/models/smart_reply/overview.md index b2363adcf48..abfcc8c2393 100644 --- a/tensorflow/lite/g3doc/models/smart_reply/overview.md +++ b/tensorflow/lite/g3doc/models/smart_reply/overview.md @@ -8,7 +8,7 @@ Our smart reply model generates reply suggestions based on chat messages. The suggestions are intended to be contextually relevant, one-touch responses that help the user to easily reply to an incoming message. -Download +Download starter model and labels ### Sample application diff --git a/tensorflow/lite/g3doc/performance/benchmarks.md b/tensorflow/lite/g3doc/performance/benchmarks.md index a51fdb40807..c7305209f69 100644 --- a/tensorflow/lite/g3doc/performance/benchmarks.md +++ b/tensorflow/lite/g3doc/performance/benchmarks.md @@ -46,7 +46,7 @@ Pixel xl | 0c | - Mobilenet_1.0_224(float) + Mobilenet_1.0_224(float) Pixel 2 123.3 ms @@ -57,7 +57,7 @@ Pixel xl | 0c | - Mobilenet_1.0_224 (quant) + Mobilenet_1.0_224 (quant) Pixel 2 65.4 ms @@ -130,14 +130,14 @@ modified to set `num_threads` to 1. - Mobilenet_1.0_224(float) + Mobilenet_1.0_224(float) iPhone 8 32.2 ms - Mobilenet_1.0_224 (quant) + Mobilenet_1.0_224 (quant) iPhone 8 24.4 ms diff --git a/tensorflow/lite/java/demo/app/build.gradle b/tensorflow/lite/java/demo/app/build.gradle index c353b2c25ca..fca18430fa5 100644 --- a/tensorflow/lite/java/demo/app/build.gradle +++ b/tensorflow/lite/java/demo/app/build.gradle @@ -60,8 +60,8 @@ dependencies { } def targetFolder = "src/main/assets" -def modelFloatDownloadUrl = "http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_224.tgz" -def modelQuantDownloadUrl = "http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz" +def modelFloatDownloadUrl = "https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_224.tgz" +def modelQuantDownloadUrl = "https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz" def localCacheFloat = "build/intermediates/mobilenet_v1_1.0_224.tgz" def localCacheQuant = "build/intermediates/mmobilenet_v1_1.0_224_quant.tgz" diff --git a/tensorflow/lite/models/smartreply/g3doc/README.md b/tensorflow/lite/models/smartreply/g3doc/README.md index 1b8ff15196c..04439293337 100644 --- a/tensorflow/lite/models/smartreply/g3doc/README.md +++ b/tensorflow/lite/models/smartreply/g3doc/README.md @@ -62,8 +62,8 @@ and [research paper](https://arxiv.org/pdf/1708.00630). ## How to use this Model? We have provided a pre-built demo APK that you can download, install and test on -your phone ([demo APK -here](http://download.tensorflow.org/deps/tflite/SmartReplyDemo.apk)). +your phone +([demo APK here](https://storage.googleapis.com/download.tensorflow.org/deps/tflite/SmartReplyDemo.apk)). The On-Device Smart Reply demo App works in the following way: diff --git a/tensorflow/lite/tools/benchmark/ios/README.md b/tensorflow/lite/tools/benchmark/ios/README.md index 3a9ae27384c..5c772ac3fca 100644 --- a/tensorflow/lite/tools/benchmark/ios/README.md +++ b/tensorflow/lite/tools/benchmark/ios/README.md @@ -13,7 +13,7 @@ parameters like inputs to the model, type of inputs, number of iterations, number of threads. The default values in the JSON file are for the Mobilenet_1.0_224 model ([paper](https://arxiv.org/pdf/1704.04861.pdf), -[tflite&pb](http://download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_224.tgz)) +[tflite&pb](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_02_22/mobilenet_v1_1.0_224.tgz)) ## To build/install/run diff --git a/tensorflow/tools/graph_transforms/README.md b/tensorflow/tools/graph_transforms/README.md index a90916cd1b9..34d6305725f 100644 --- a/tensorflow/tools/graph_transforms/README.md +++ b/tensorflow/tools/graph_transforms/README.md @@ -111,7 +111,7 @@ unsure, the tool can inspect the model and provide guesses about likely input and output nodes, as well as other information that's useful for debugging. Here's an example of how to use it on the [Inception V3 -graph](http://download.tensorflow.org/models/image/imagenet/inception-2015-12-05.tgz): +graph](https://storage.googleapis.com/download.tensorflow.org/models/image/imagenet/inception-2015-12-05.tgz): ```bash bazel build tensorflow/tools/graph_transforms:summarize_graph @@ -124,7 +124,7 @@ This section has small guides for some of the most frequently-used transformation pipelines, aimed at users who want to quickly accomplish one of these tasks. A lot of them will use the Inception V3 model for their examples, which can be downloaded from -[http://download.tensorflow.org/models/image/imagenet/inception-2015-12-05.tgz](http://download.tensorflow.org/models/image/imagenet/inception-2015-12-05.tgz). +[https://storage.googleapis.com/download.tensorflow.org/models/image/imagenet/inception-2015-12-05.tgz](https://storage.googleapis.com/download.tensorflow.org/models/image/imagenet/inception-2015-12-05.tgz). ### Optimizing for Deployment diff --git a/tensorflow/workspace.bzl b/tensorflow/workspace.bzl index f888e2d8b83..a22708b4016 100755 --- a/tensorflow/workspace.bzl +++ b/tensorflow/workspace.bzl @@ -787,8 +787,8 @@ def tf_repositories(path_prefix = "", tf_repo_name = ""): build_file = clean_dep("//third_party:tflite_mobilenet_float.BUILD"), sha256 = "2fadeabb9968ec6833bee903900dda6e61b3947200535874ce2fe42a8493abc0", urls = [ - "http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224.tgz", - "http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224.tgz", + "https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224.tgz", + "https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224.tgz", ], ) @@ -797,8 +797,8 @@ def tf_repositories(path_prefix = "", tf_repo_name = ""): build_file = clean_dep("//third_party:tflite_mobilenet_quant.BUILD"), sha256 = "d32432d28673a936b2d6281ab0600c71cf7226dfe4cdcef3012555f691744166", urls = [ - "http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz", - "http://download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz", + "https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz", + "https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz", ], )