diff options
author | Dandelion Man? <dandelion@google.com> | 2017-12-15 17:12:41 -0800 |
---|---|---|
committer | TensorFlower Gardener <gardener@tensorflow.org> | 2017-12-15 17:16:29 -0800 |
commit | d55f532867a3670d66460c5ee3b774519542adc1 (patch) | |
tree | 7de4d85bcd61e93401459276b4d371ab0be23c1f /tensorflow/examples | |
parent | 32d5048ae96116202f2aa0fa739ef37514ee8a54 (diff) |
Merge changes from github.
PiperOrigin-RevId: 179258973
Diffstat (limited to 'tensorflow/examples')
-rw-r--r-- | tensorflow/examples/android/build.gradle | 6 | ||||
-rw-r--r-- | tensorflow/examples/android/gradle/wrapper/gradle-wrapper.jar | bin | 0 -> 53636 bytes | |||
-rw-r--r-- | tensorflow/examples/android/gradle/wrapper/gradle-wrapper.properties | 6 | ||||
-rw-r--r-- | tensorflow/examples/android/gradlew | 160 | ||||
-rw-r--r-- | tensorflow/examples/android/gradlew.bat | 90 | ||||
-rw-r--r-- | tensorflow/examples/android/src/org/tensorflow/demo/CameraActivity.java | 8 | ||||
-rw-r--r-- | tensorflow/examples/how_tos/reading_data/fully_connected_reader.py | 125 | ||||
-rw-r--r-- | tensorflow/examples/wav_to_spectrogram/wav_to_spectrogram.cc | 7 |
8 files changed, 326 insertions, 76 deletions
diff --git a/tensorflow/examples/android/build.gradle b/tensorflow/examples/android/build.gradle index 48f566f825..f7bdf8b816 100644 --- a/tensorflow/examples/android/build.gradle +++ b/tensorflow/examples/android/build.gradle @@ -28,8 +28,8 @@ buildscript { } dependencies { - classpath 'com.android.tools.build:gradle:2.3.0' - classpath 'org.apache.httpcomponents:httpclient:4.5.2' + classpath 'com.android.tools.build:gradle:3.0.1' + classpath 'org.apache.httpcomponents:httpclient:4.5.4' } } @@ -75,7 +75,7 @@ apply plugin: 'com.android.application' android { compileSdkVersion 23 - buildToolsVersion "25.0.2" + buildToolsVersion '26.0.2' if (nativeBuildSystem == 'cmake') { defaultConfig { diff --git a/tensorflow/examples/android/gradle/wrapper/gradle-wrapper.jar b/tensorflow/examples/android/gradle/wrapper/gradle-wrapper.jar Binary files differnew file mode 100644 index 0000000000..13372aef5e --- /dev/null +++ b/tensorflow/examples/android/gradle/wrapper/gradle-wrapper.jar diff --git a/tensorflow/examples/android/gradle/wrapper/gradle-wrapper.properties b/tensorflow/examples/android/gradle/wrapper/gradle-wrapper.properties new file mode 100644 index 0000000000..bd9ee87db3 --- /dev/null +++ b/tensorflow/examples/android/gradle/wrapper/gradle-wrapper.properties @@ -0,0 +1,6 @@ +#Sat Nov 18 15:06:47 CET 2017 +distributionBase=GRADLE_USER_HOME +distributionPath=wrapper/dists +zipStoreBase=GRADLE_USER_HOME +zipStorePath=wrapper/dists +distributionUrl=https\://services.gradle.org/distributions/gradle-4.1-all.zip diff --git a/tensorflow/examples/android/gradlew b/tensorflow/examples/android/gradlew new file mode 100644 index 0000000000..9d82f78915 --- /dev/null +++ b/tensorflow/examples/android/gradlew @@ -0,0 +1,160 @@ +#!/usr/bin/env bash + +############################################################################## +## +## Gradle start up script for UN*X +## +############################################################################## + +# Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script. +DEFAULT_JVM_OPTS="" + +APP_NAME="Gradle" +APP_BASE_NAME=`basename "$0"` + +# Use the maximum available, or set MAX_FD != -1 to use that value. +MAX_FD="maximum" + +warn ( ) { + echo "$*" +} + +die ( ) { + echo + echo "$*" + echo + exit 1 +} + +# OS specific support (must be 'true' or 'false'). +cygwin=false +msys=false +darwin=false +case "`uname`" in + CYGWIN* ) + cygwin=true + ;; + Darwin* ) + darwin=true + ;; + MINGW* ) + msys=true + ;; +esac + +# Attempt to set APP_HOME +# Resolve links: $0 may be a link +PRG="$0" +# Need this for relative symlinks. +while [ -h "$PRG" ] ; do + ls=`ls -ld "$PRG"` + link=`expr "$ls" : '.*-> \(.*\)$'` + if expr "$link" : '/.*' > /dev/null; then + PRG="$link" + else + PRG=`dirname "$PRG"`"/$link" + fi +done +SAVED="`pwd`" +cd "`dirname \"$PRG\"`/" >/dev/null +APP_HOME="`pwd -P`" +cd "$SAVED" >/dev/null + +CLASSPATH=$APP_HOME/gradle/wrapper/gradle-wrapper.jar + +# Determine the Java command to use to start the JVM. +if [ -n "$JAVA_HOME" ] ; then + if [ -x "$JAVA_HOME/jre/sh/java" ] ; then + # IBM's JDK on AIX uses strange locations for the executables + JAVACMD="$JAVA_HOME/jre/sh/java" + else + JAVACMD="$JAVA_HOME/bin/java" + fi + if [ ! -x "$JAVACMD" ] ; then + die "ERROR: JAVA_HOME is set to an invalid directory: $JAVA_HOME + +Please set the JAVA_HOME variable in your environment to match the +location of your Java installation." + fi +else + JAVACMD="java" + which java >/dev/null 2>&1 || die "ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH. + +Please set the JAVA_HOME variable in your environment to match the +location of your Java installation." +fi + +# Increase the maximum file descriptors if we can. +if [ "$cygwin" = "false" -a "$darwin" = "false" ] ; then + MAX_FD_LIMIT=`ulimit -H -n` + if [ $? -eq 0 ] ; then + if [ "$MAX_FD" = "maximum" -o "$MAX_FD" = "max" ] ; then + MAX_FD="$MAX_FD_LIMIT" + fi + ulimit -n $MAX_FD + if [ $? -ne 0 ] ; then + warn "Could not set maximum file descriptor limit: $MAX_FD" + fi + else + warn "Could not query maximum file descriptor limit: $MAX_FD_LIMIT" + fi +fi + +# For Darwin, add options to specify how the application appears in the dock +if $darwin; then + GRADLE_OPTS="$GRADLE_OPTS \"-Xdock:name=$APP_NAME\" \"-Xdock:icon=$APP_HOME/media/gradle.icns\"" +fi + +# For Cygwin, switch paths to Windows format before running java +if $cygwin ; then + APP_HOME=`cygpath --path --mixed "$APP_HOME"` + CLASSPATH=`cygpath --path --mixed "$CLASSPATH"` + JAVACMD=`cygpath --unix "$JAVACMD"` + + # We build the pattern for arguments to be converted via cygpath + ROOTDIRSRAW=`find -L / -maxdepth 1 -mindepth 1 -type d 2>/dev/null` + SEP="" + for dir in $ROOTDIRSRAW ; do + ROOTDIRS="$ROOTDIRS$SEP$dir" + SEP="|" + done + OURCYGPATTERN="(^($ROOTDIRS))" + # Add a user-defined pattern to the cygpath arguments + if [ "$GRADLE_CYGPATTERN" != "" ] ; then + OURCYGPATTERN="$OURCYGPATTERN|($GRADLE_CYGPATTERN)" + fi + # Now convert the arguments - kludge to limit ourselves to /bin/sh + i=0 + for arg in "$@" ; do + CHECK=`echo "$arg"|egrep -c "$OURCYGPATTERN" -` + CHECK2=`echo "$arg"|egrep -c "^-"` ### Determine if an option + + if [ $CHECK -ne 0 ] && [ $CHECK2 -eq 0 ] ; then ### Added a condition + eval `echo args$i`=`cygpath --path --ignore --mixed "$arg"` + else + eval `echo args$i`="\"$arg\"" + fi + i=$((i+1)) + done + case $i in + (0) set -- ;; + (1) set -- "$args0" ;; + (2) set -- "$args0" "$args1" ;; + (3) set -- "$args0" "$args1" "$args2" ;; + (4) set -- "$args0" "$args1" "$args2" "$args3" ;; + (5) set -- "$args0" "$args1" "$args2" "$args3" "$args4" ;; + (6) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" ;; + (7) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" ;; + (8) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" "$args7" ;; + (9) set -- "$args0" "$args1" "$args2" "$args3" "$args4" "$args5" "$args6" "$args7" "$args8" ;; + esac +fi + +# Split up the JVM_OPTS And GRADLE_OPTS values into an array, following the shell quoting and substitution rules +function splitJvmOpts() { + JVM_OPTS=("$@") +} +eval splitJvmOpts $DEFAULT_JVM_OPTS $JAVA_OPTS $GRADLE_OPTS +JVM_OPTS[${#JVM_OPTS[*]}]="-Dorg.gradle.appname=$APP_BASE_NAME" + +exec "$JAVACMD" "${JVM_OPTS[@]}" -classpath "$CLASSPATH" org.gradle.wrapper.GradleWrapperMain "$@" diff --git a/tensorflow/examples/android/gradlew.bat b/tensorflow/examples/android/gradlew.bat new file mode 100644 index 0000000000..8a0b282aa6 --- /dev/null +++ b/tensorflow/examples/android/gradlew.bat @@ -0,0 +1,90 @@ +@if "%DEBUG%" == "" @echo off +@rem ########################################################################## +@rem +@rem Gradle startup script for Windows +@rem +@rem ########################################################################## + +@rem Set local scope for the variables with windows NT shell +if "%OS%"=="Windows_NT" setlocal + +@rem Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script. +set DEFAULT_JVM_OPTS= + +set DIRNAME=%~dp0 +if "%DIRNAME%" == "" set DIRNAME=. +set APP_BASE_NAME=%~n0 +set APP_HOME=%DIRNAME% + +@rem Find java.exe +if defined JAVA_HOME goto findJavaFromJavaHome + +set JAVA_EXE=java.exe +%JAVA_EXE% -version >NUL 2>&1 +if "%ERRORLEVEL%" == "0" goto init + +echo. +echo ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH. +echo. +echo Please set the JAVA_HOME variable in your environment to match the +echo location of your Java installation. + +goto fail + +:findJavaFromJavaHome +set JAVA_HOME=%JAVA_HOME:"=% +set JAVA_EXE=%JAVA_HOME%/bin/java.exe + +if exist "%JAVA_EXE%" goto init + +echo. +echo ERROR: JAVA_HOME is set to an invalid directory: %JAVA_HOME% +echo. +echo Please set the JAVA_HOME variable in your environment to match the +echo location of your Java installation. + +goto fail + +:init +@rem Get command-line arguments, handling Windowz variants + +if not "%OS%" == "Windows_NT" goto win9xME_args +if "%@eval[2+2]" == "4" goto 4NT_args + +:win9xME_args +@rem Slurp the command line arguments. +set CMD_LINE_ARGS= +set _SKIP=2 + +:win9xME_args_slurp +if "x%~1" == "x" goto execute + +set CMD_LINE_ARGS=%* +goto execute + +:4NT_args +@rem Get arguments from the 4NT Shell from JP Software +set CMD_LINE_ARGS=%$ + +:execute +@rem Setup the command line + +set CLASSPATH=%APP_HOME%\gradle\wrapper\gradle-wrapper.jar + +@rem Execute Gradle +"%JAVA_EXE%" %DEFAULT_JVM_OPTS% %JAVA_OPTS% %GRADLE_OPTS% "-Dorg.gradle.appname=%APP_BASE_NAME%" -classpath "%CLASSPATH%" org.gradle.wrapper.GradleWrapperMain %CMD_LINE_ARGS% + +:end +@rem End local scope for the variables with windows NT shell +if "%ERRORLEVEL%"=="0" goto mainEnd + +:fail +rem Set variable GRADLE_EXIT_CONSOLE if you need the _script_ return code instead of +rem the _cmd.exe /c_ return code! +if not "" == "%GRADLE_EXIT_CONSOLE%" exit 1 +exit /b 1 + +:mainEnd +if "%OS%"=="Windows_NT" endlocal + +:omega diff --git a/tensorflow/examples/android/src/org/tensorflow/demo/CameraActivity.java b/tensorflow/examples/android/src/org/tensorflow/demo/CameraActivity.java index 4e45f42d0c..8bd4abb154 100644 --- a/tensorflow/examples/android/src/org/tensorflow/demo/CameraActivity.java +++ b/tensorflow/examples/android/src/org/tensorflow/demo/CameraActivity.java @@ -333,8 +333,12 @@ public abstract class CameraActivity extends Activity continue; } - useCamera2API = isHardwareLevelSupported(characteristics, - CameraCharacteristics.INFO_SUPPORTED_HARDWARE_LEVEL_FULL); + // Fallback to camera1 API for internal cameras that don't have full support. + // This should help with legacy situations where using the camera2 API causes + // distorted or otherwise broken previews. + useCamera2API = (facing == CameraCharacteristics.LENS_FACING_EXTERNAL) + || isHardwareLevelSupported(characteristics, + CameraCharacteristics.INFO_SUPPORTED_HARDWARE_LEVEL_FULL); LOGGER.i("Camera API lv2?: %s", useCamera2API); return cameraId; } diff --git a/tensorflow/examples/how_tos/reading_data/fully_connected_reader.py b/tensorflow/examples/how_tos/reading_data/fully_connected_reader.py index a9ed02dd1a..9db8835d92 100644 --- a/tensorflow/examples/how_tos/reading_data/fully_connected_reader.py +++ b/tensorflow/examples/how_tos/reading_data/fully_connected_reader.py @@ -45,9 +45,7 @@ TRAIN_FILE = 'train.tfrecords' VALIDATION_FILE = 'validation.tfrecords' -def read_and_decode(filename_queue): - reader = tf.TFRecordReader() - _, serialized_example = reader.read(filename_queue) +def decode(serialized_example): features = tf.parse_single_example( serialized_example, # Defaults are not specified since both keys are required. @@ -60,22 +58,26 @@ def read_and_decode(filename_queue): # length mnist.IMAGE_PIXELS) to a uint8 tensor with shape # [mnist.IMAGE_PIXELS]. image = tf.decode_raw(features['image_raw'], tf.uint8) - image.set_shape([mnist.IMAGE_PIXELS]) + image.set_shape((mnist.IMAGE_PIXELS)) + # Convert label from a scalar uint8 tensor to an int32 scalar. + label = tf.cast(features['label'], tf.int32) + + return image, label + +def augment(image, label): # OPTIONAL: Could reshape into a 28x28 image and apply distortions # here. Since we are not applying any distortions in this # example, and the next step expects the image to be flattened # into a vector, we don't bother. + return image, label +def normalize(image, label): # Convert from [0, 255] -> [-0.5, 0.5] floats. image = tf.cast(image, tf.float32) * (1. / 255) - 0.5 - # Convert label from a scalar uint8 tensor to an int32 scalar. - label = tf.cast(features['label'], tf.int32) - return image, label - def inputs(train, batch_size, num_epochs): """Reads input data num_epochs times. @@ -91,31 +93,32 @@ def inputs(train, batch_size, num_epochs): in the range [-0.5, 0.5]. * labels is an int32 tensor with shape [batch_size] with the true label, a number in the range [0, mnist.NUM_CLASSES). - Note that an tf.train.QueueRunner is added to the graph, which - must be run using e.g. tf.train.start_queue_runners(). + + This function creates a one_shot_iterator, meaning that it will only iterate + over the dataset once. On the other hand there is no special initialization + required. """ if not num_epochs: num_epochs = None filename = os.path.join(FLAGS.train_dir, TRAIN_FILE if train else VALIDATION_FILE) with tf.name_scope('input'): - filename_queue = tf.train.string_input_producer( - [filename], num_epochs=num_epochs) + # TFRecordDataset opens a protobuf and reads entries line by line + # could also be [list, of, filenames] + dataset = tf.data.TFRecordDataset(filename) + dataset = dataset.repeat(num_epochs) - # Even when reading in multiple threads, share the filename - # queue. - image, label = read_and_decode(filename_queue) + # map takes a python function and applies it to every sample + dataset = dataset.map(decode) + dataset = dataset.map(augment) + dataset = dataset.map(normalize) - # Shuffle the examples and collect them into batch_size batches. - # (Internally uses a RandomShuffleQueue.) - # We run this in two threads to avoid being a bottleneck. - images, sparse_labels = tf.train.shuffle_batch( - [image, label], batch_size=batch_size, num_threads=2, - capacity=1000 + 3 * batch_size, - # Ensures a minimum amount of shuffling of examples. - min_after_dequeue=1000) + #the parameter is the queue size + dataset = dataset.shuffle(1000 + 3 * batch_size) + dataset = dataset.batch(batch_size) - return images, sparse_labels + iterator = dataset.make_one_shot_iterator() + return iterator.get_next() def run_training(): @@ -124,16 +127,16 @@ def run_training(): # Tell TensorFlow that the model will be built into the default Graph. with tf.Graph().as_default(): # Input images and labels. - images, labels = inputs(train=True, batch_size=FLAGS.batch_size, - num_epochs=FLAGS.num_epochs) + image_batch, label_batch = inputs(train=True, batch_size=FLAGS.batch_size, + num_epochs=FLAGS.num_epochs) # Build a Graph that computes predictions from the inference model. - logits = mnist.inference(images, + logits = mnist.inference(image_batch, FLAGS.hidden1, FLAGS.hidden2) # Add to the Graph the loss calculation. - loss = mnist.loss(logits, labels) + loss = mnist.loss(logits, label_batch) # Add to the Graph operations that train the model. train_op = mnist.training(loss, FLAGS.learning_rate) @@ -143,47 +146,33 @@ def run_training(): tf.local_variables_initializer()) # Create a session for running operations in the Graph. - sess = tf.Session() - - # Initialize the variables (the trained variables and the - # epoch counter). - sess.run(init_op) - - # Start input enqueue threads. - coord = tf.train.Coordinator() - threads = tf.train.start_queue_runners(sess=sess, coord=coord) - - try: - step = 0 - while not coord.should_stop(): - start_time = time.time() - - # Run one step of the model. The return values are - # the activations from the `train_op` (which is - # discarded) and the `loss` op. To inspect the values - # of your ops or variables, you may include them in - # the list passed to sess.run() and the value tensors - # will be returned in the tuple from the call. - _, loss_value = sess.run([train_op, loss]) - - duration = time.time() - start_time - - # Print an overview fairly often. - if step % 100 == 0: - print('Step %d: loss = %.2f (%.3f sec)' % (step, loss_value, + with tf.Session() as sess: + # Initialize the variables (the trained variables and the + # epoch counter). + sess.run(init_op) + try: + step = 0 + while True: #train until OutOfRangeError + start_time = time.time() + + # Run one step of the model. The return values are + # the activations from the `train_op` (which is + # discarded) and the `loss` op. To inspect the values + # of your ops or variables, you may include them in + # the list passed to sess.run() and the value tensors + # will be returned in the tuple from the call. + _, loss_value = sess.run([train_op, loss]) + + duration = time.time() - start_time + + # Print an overview fairly often. + if step % 100 == 0: + print('Step %d: loss = %.2f (%.3f sec)' % (step, loss_value, duration)) - step += 1 - except tf.errors.OutOfRangeError: - print('Done training for %d epochs, %d steps.' % (FLAGS.num_epochs, step)) - finally: - # When done, ask the threads to stop. - coord.request_stop() - - # Wait for threads to finish. - coord.join(threads) - sess.close() - - + step += 1 + except tf.errors.OutOfRangeError: + print('Done training for %d epochs, %d steps.' % (FLAGS.num_epochs, step)) + def main(_): run_training() diff --git a/tensorflow/examples/wav_to_spectrogram/wav_to_spectrogram.cc b/tensorflow/examples/wav_to_spectrogram/wav_to_spectrogram.cc index 1e375ed48e..4a429837b7 100644 --- a/tensorflow/examples/wav_to_spectrogram/wav_to_spectrogram.cc +++ b/tensorflow/examples/wav_to_spectrogram/wav_to_spectrogram.cc @@ -53,7 +53,8 @@ tensorflow::Status WavToSpectrogram(const tensorflow::string& input_wav, // - Scales, clamps, and converts that spectrogram to 0 to 255 uint8's. // - Reshapes the tensor so that it's [height, width, 1] for imaging. // - Encodes it as a PNG stream and saves it out to a file. - Output file_reader = ReadFile(root.WithOpName("input_wav"), input_wav); + Output file_reader = + tensorflow::ops::ReadFile(root.WithOpName("input_wav"), input_wav); DecodeWav wav_decoder = DecodeWav(root.WithOpName("wav_decoder"), file_reader); Output spectrogram = AudioSpectrogram(root.WithOpName("spectrogram"), @@ -71,8 +72,8 @@ tensorflow::Status WavToSpectrogram(const tensorflow::string& input_wav, Output squeeze = Squeeze(root.WithOpName("squeeze"), expand_dims, Squeeze::Attrs().Axis({0})); Output png_encoder = EncodePng(root.WithOpName("png_encoder"), squeeze); - WriteFile file_writer = - WriteFile(root.WithOpName("output_image"), output_image, png_encoder); + tensorflow::ops::WriteFile file_writer = tensorflow::ops::WriteFile( + root.WithOpName("output_image"), output_image, png_encoder); tensorflow::GraphDef graph; TF_RETURN_IF_ERROR(root.ToGraphDef(&graph)); |