tensorflow | An Open Source Machine Learning Framework for Everyone | Machine Learning library

// A convenient interface for building up computations.

XlaOp ConstantLiteral(XlaBuilder* builder, const LiteralSlice& literal);

F tensorflow/core/platform/statusor.cc:33] Attempting to fetch value instead of handling error Invalid argument: No XlaOp with handle -1

@sock.route('/api')
def echo(sock):
    while True:
        # get user input from browser
        user_input = sock.receive()
        # print user input on console
        print(user_input)
        # read answer from console
        response = input()
        # send response to browser
        sock.send(response)

while True:
    question = input("")
    ints = predict(question)
    answer = response(ints, json_data)
    print(answer)

def predict(sentence):
    bag_of_words = convert_sentence_in_bag_of_words(sentence)
    # pass bag as list and get index 0
    prediction = model.predict(np.array([bag_of_words]))[0]
    ERROR_THRESHOLD = 0.25
    accepted_results = [[tag, probability] for tag, probability in enumerate(prediction) if probability > ERROR_THRESHOLD]

    accepted_results.sort(key=lambda x: x[1], reverse=True)

    output = []
    for accepted_result in accepted_results:
        output.append({'intent': classes[accepted_result[0]], 'probability': str(accepted_result[1])})
        print(output)
    return output


def response(intents, json):
    tag = intents[0]['intent']
    intents_as_list = json['intents']
    for i in intents_as_list:
        if i['tag'] == tag:
            res = random.choice(i['responses'])
            break
    return res

 * Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)
 * Restarting with stat
 * Serving Flask app 'server' (lazy loading)
 * Environment: production
   WARNING: This is a development server. Do not use it in a production deployment.
   Use a production WSGI server instead.
 * Debug mode: on

2022-02-13 11:31:38.887640: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:305] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support.
2022-02-13 11:31:38.887734: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:271] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical PluggableDevice (device: 0, name: METAL, pci bus id: <undefined>)
Metal device set to: Apple M1

systemMemory: 16.00 GB
maxCacheSize: 5.33 GB

plugins {
    id 'com.android.application'
    id 'kotlin-android'
}

android {
    compileSdkVersion 30
    buildToolsVersion "30.0.3"

    defaultConfig {
        applicationId "com.example.retrofit_test"
        minSdkVersion 21
        targetSdkVersion 30
        versionCode 1
        versionName "1.0"

        testInstrumentationRunner "androidx.test.runner.AndroidJUnitRunner"
    }

    buildTypes {
        release {
            minifyEnabled false
            proguardFiles getDefaultProguardFile('proguard-android-optimize.txt'), 'proguard-rules.pro'
        }
    }
    compileOptions {
        sourceCompatibility JavaVersion.VERSION_1_8
        targetCompatibility JavaVersion.VERSION_1_8
    }
    kotlinOptions {
        jvmTarget = '1.8'
    }
}

dependencies {

//    implementation 'com.google.guava:guava:30.1.1-jre'
    implementation 'com.google.guava:guava:30.1-jre'

//    implementation 'org.jetbrains.kotlin:kotlin-stdlib:1.5.30-M1'

    implementation 'androidx.core:core-ktx:1.6.0'
    implementation 'androidx.appcompat:appcompat:1.3.1'
    implementation 'com.google.android.material:material:1.4.0'
    implementation 'androidx.constraintlayout:constraintlayout:2.1.0'
    implementation 'androidx.navigation:navigation-fragment-ktx:2.3.5'
    implementation 'androidx.navigation:navigation-ui-ktx:2.3.5'
    implementation 'androidx.lifecycle:lifecycle-livedata-ktx:2.3.1'
    implementation 'androidx.lifecycle:lifecycle-viewmodel-ktx:2.3.1'
    implementation 'androidx.navigation:navigation-fragment-ktx:2.3.5'
    implementation 'androidx.navigation:navigation-ui-ktx:2.3.5'

    implementation 'com.squareup.retrofit2:retrofit:2.9.0'
    implementation 'com.google.code.gson:gson:2.8.7'
    implementation 'com.squareup.retrofit2:converter-gson:2.9.0'
    implementation 'com.squareup.okhttp3:logging-interceptor:4.9.1'

    implementation 'com.github.bumptech.glide:glide:4.12.0'
    implementation 'android.arch.persistence.room:guava:1.1.1'
    annotationProcessor 'com.github.bumptech.glide:compiler:4.11.0'

    testImplementation 'junit:junit:4.13.2'
    androidTestImplementation 'androidx.test.ext:junit:1.1.3'
    androidTestImplementation 'androidx.test.espresso:espresso-core:3.4.0'
}

   Could not resolve all artifacts for configuration ':classpath'.
   Could not find org.jetbrains.kotlin:kotlin-gradle-plugin:1.5.30.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/org/jetbrains/kotlin/kotlin-gradle-plugin/1.5.30/kotlin-gradle-plugin-1.5.30.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project :
   Could not find org.jetbrains.kotlin:kotlin-stdlib-jdk8:1.4.32.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/org/jetbrains/kotlin/kotlin-stdlib-jdk8/1.4.32/kotlin-stdlib-jdk8-1.4.32.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools:sdk-common:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools:repository:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:aaptcompiler:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.analytics-library:shared:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.lint:lint-model:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > androidx.databinding:databinding-compiler-common:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.utp:android-test-plugin-host-retention-proto:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:builder:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:builder-model:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:gradle-api:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools:sdk-common:30.0.2 > com.android.tools:common:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:builder:7.0.2 > com.android.tools.analytics-library:tracker:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:builder:7.0.2 > com.android.tools.build:manifest-merger:30.0.2
   Could not find org.apache.httpcomponents:httpmime:4.5.6.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/org/apache/httpcomponents/httpmime/4.5.6/httpmime-4.5.6.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools:sdklib:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.analytics-library:crash:30.0.2
   Could not find commons-io:commons-io:2.4.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/commons-io/commons-io/2.4/commons-io-2.4.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > androidx.databinding:databinding-compiler-common:7.0.2
   Could not find org.ow2.asm:asm:7.0.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/org/ow2/asm/asm/7.0/asm-7.0.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:builder:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:gradle-api:7.0.2
   Could not find org.ow2.asm:asm-analysis:7.0.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/org/ow2/asm/asm-analysis/7.0/asm-analysis-7.0.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
   Could not find org.ow2.asm:asm-commons:7.0.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/org/ow2/asm/asm-commons/7.0/asm-commons-7.0.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:builder:7.0.2
   Could not find org.ow2.asm:asm-util:7.0.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/org/ow2/asm/asm-util/7.0/asm-util-7.0.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:builder:7.0.2
   Could not find org.bouncycastle:bcpkix-jdk15on:1.56.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/org/bouncycastle/bcpkix-jdk15on/1.56/bcpkix-jdk15on-1.56.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools:sdk-common:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:builder:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:builder:7.0.2 > com.android.tools.build:apkzlib:7.0.2
   Could not find org.glassfish.jaxb:jaxb-runtime:2.3.2.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/org/glassfish/jaxb/jaxb-runtime/2.3.2/jaxb-runtime-2.3.2.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools:sdk-common:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools:sdklib:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools:repository:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > androidx.databinding:databinding-compiler-common:7.0.2
   Could not find net.sf.jopt-simple:jopt-simple:4.9.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/net/sf/jopt-simple/jopt-simple/4.9/jopt-simple-4.9.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:builder:7.0.2
   Could not find com.squareup:javapoet:1.10.0.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/com/squareup/javapoet/1.10.0/javapoet-1.10.0.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > androidx.databinding:databinding-compiler-common:7.0.2
   Could not find com.google.protobuf:protobuf-java:3.10.0.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/com/google/protobuf/protobuf-java/3.10.0/protobuf-java-3.10.0.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools:sdk-common:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.ddms:ddmlib:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:aapt2-proto:7.0.2-7396180
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:aaptcompiler:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.utp:android-device-provider-gradle-proto:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.utp:android-test-plugin-host-retention-proto:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.utp:android-test-plugin-result-listener-gradle-proto:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:bundletool:1.6.0
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.analytics-library:shared:30.0.2 > com.android.tools.analytics-library:protos:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:builder:7.0.2 > com.android.tools.analytics-library:tracker:30.0.2
   Could not find com.google.protobuf:protobuf-java-util:3.10.0.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/com/google/protobuf/protobuf-java-util/3.10.0/protobuf-java-util-3.10.0.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:bundletool:1.6.0
   Could not find com.google.code.gson:gson:2.8.6.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/com/google/code/gson/gson/2.8.6/gson-2.8.6.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools:sdk-common:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools:sdklib:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.analytics-library:shared:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > androidx.databinding:databinding-compiler-common:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.utp:android-test-plugin-result-listener-gradle-proto:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:builder:7.0.2 > com.android.tools.build:manifest-merger:30.0.2
   Could not find io.grpc:grpc-core:1.21.1.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/io/grpc/grpc-core/1.21.1/grpc-core-1.21.1.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.utp:android-test-plugin-result-listener-gradle-proto:30.0.2
   Could not find io.grpc:grpc-netty:1.21.1.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/io/grpc/grpc-netty/1.21.1/grpc-netty-1.21.1.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.utp:android-test-plugin-result-listener-gradle-proto:30.0.2
   Could not find io.grpc:grpc-protobuf:1.21.1.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/io/grpc/grpc-protobuf/1.21.1/grpc-protobuf-1.21.1.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.utp:android-test-plugin-result-listener-gradle-proto:30.0.2
   Could not find io.grpc:grpc-stub:1.21.1.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/io/grpc/grpc-stub/1.21.1/grpc-stub-1.21.1.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.utp:android-test-plugin-result-listener-gradle-proto:30.0.2
   Could not find com.google.crypto.tink:tink:1.3.0-rc2.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/com/google/crypto/tink/tink/1.3.0-rc2/tink-1.3.0-rc2.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
   Could not find com.google.flatbuffers:flatbuffers-java:1.12.0.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/com/google/flatbuffers/flatbuffers-java/1.12.0/flatbuffers-java-1.12.0.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
   Could not find org.tensorflow:tensorflow-lite-metadata:0.1.0-rc2.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/org/tensorflow/tensorflow-lite-metadata/0.1.0-rc2/tensorflow-lite-metadata-0.1.0-rc2.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2
   Could not find org.bouncycastle:bcprov-jdk15on:1.56.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/org/bouncycastle/bcprov-jdk15on/1.56/bcprov-jdk15on-1.56.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools:sdk-common:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:builder:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:builder:7.0.2 > com.android.tools.build:apkzlib:7.0.2
   Could not find com.google.guava:guava:30.1-jre.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/com/google/guava/guava/30.1-jre/guava-30.1-jre.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools:sdk-common:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:aaptcompiler:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.analytics-library:crash:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.analytics-library:shared:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > androidx.databinding:databinding-compiler-common:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:builder-test-api:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.utp:android-test-plugin-result-listener-gradle-proto:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:bundletool:1.6.0
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:gradle-api:7.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools:sdk-common:30.0.2 > com.android.tools:common:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:builder:7.0.2 > com.android.tools.analytics-library:tracker:30.0.2
   Could not find org.jetbrains.kotlin:kotlin-reflect:1.4.32.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/org/jetbrains/kotlin/kotlin-reflect/1.4.32/kotlin-reflect-1.4.32.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools:sdk-common:30.0.2
   Could not find javax.inject:javax.inject:1.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/javax/inject/javax.inject/1/javax.inject-1.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools:sdk-common:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:bundletool:1.6.0
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:builder:7.0.2
   Could not find net.sf.kxml:kxml2:2.3.0.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/net/sf/kxml/kxml2/2.3.0/kxml2-2.3.0.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools:sdk-common:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.ddms:ddmlib:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.lint:lint-model:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.layoutlib:layoutlib-api:30.0.2
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools.build:builder:7.0.2 > com.android.tools.build:manifest-merger:30.0.2
   Could not find org.jetbrains.intellij.deps:trove4j:1.0.20181211.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/org/jetbrains/intellij/deps/trove4j/1.0.20181211/trove4j-1.0.20181211.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools:sdk-common:30.0.2
   Could not find xerces:xercesImpl:2.12.0.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/xerces/xercesImpl/2.12.0/xercesImpl-2.12.0.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.
     Required by:
         project : > com.android.tools.build:gradle:7.0.2 > com.android.tools:sdk-common:30.0.2
   Could not find org.apache.commons:commons-compress:1.20.
     Searched in the following locations:
       - https://dl.google.com/dl/android/maven2/org/apache/commons/commons-compress/1.20/commons-compress-1.20.pom
     If the artifact you are trying to retrieve can be found in the repository but without metadata in 'Maven POM' format, you need to adjust the 'metadataSources { ... }' of the repository declaration.

devtools::install_github("rstudio/reticulate")
devtools::install_github("rstudio/keras") # This package also installs tensorflow
library(reticulate)
reticulate::install_miniconda()
reticulate::use_miniconda("r-reticulate")
library(tensorflow)
tensorflow::tf_config() **# Crashes at this point**

sessionInfo()


R version 3.6.0 (2019-04-26)
Platform: x86_64-redhat-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS/LAPACK: /usr/lib64/R/lib/libRblas.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] tensorflow_2.7.0.9000 keras_2.7.0.9000      reticulate_1.22-9000 

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.7      lattice_0.20-45 png_0.1-7       zeallot_0.1.0  
 [5] rappdirs_0.3.3  grid_3.6.0      R6_2.5.1        jsonlite_1.7.2 
 [9] magrittr_2.0.1  tfruns_1.5.0    rlang_0.4.12    whisker_0.4    
[13] Matrix_1.3-4    generics_0.1.1  tools_3.6.0     compiler_3.6.0 
[17] base64enc_0.1-3

conda create --name py38 python=3.8.0
conda activate py38
conda install tensorflow=2.4

devtools::install_github("rstudio/reticulate")
library(reticulate)
reticulate::use_condaenv("/root/.conda/envs/py38", required = TRUE)
reticulate::use_python("/root/.conda/envs/py38/bin/python3.8", required = TRUE)
reticulate::py_available(initialize = TRUE)
ts <- reticulate::import("tensorflow")

Error in py_module_import(module, convert = convert) : 
  ImportError: Traceback (most recent call last):
  File "/root/.conda/envs/py38/lib/python3.8/site-packages/tensorflow/python/pywrap_tensorflow.py", line 64, in <module>
    from tensorflow.python._pywrap_tensorflow_internal import *
  File "/home/R/x86_64-redhat-linux-gnu-library/3.6/reticulate/python/rpytools/loader.py", line 39, in _import_hook
    module = _import(
ImportError: /lib64/libstdc++.so.6: version `GLIBCXX_3.4.20' not found (required by /root/.conda/envs/py38/lib/python3.8/site-packages/tensorflow/python/_pywrap_tensorflow_internal.so)


Failed to load the native TensorFlow runtime.

See https://www.tensorflow.org/install/errors

for some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.

> strings /lib64/libstdc++.so.6 | grep GLIBC

GLIBCXX_3.4
GLIBCXX_3.4.1
GLIBCXX_3.4.2
GLIBCXX_3.4.3
GLIBCXX_3.4.4
GLIBCXX_3.4.5
GLIBCXX_3.4.6
GLIBCXX_3.4.7
GLIBCXX_3.4.8
GLIBCXX_3.4.9
GLIBCXX_3.4.10
GLIBCXX_3.4.11
GLIBCXX_3.4.12
GLIBCXX_3.4.13
GLIBCXX_3.4.14
GLIBCXX_3.4.15
GLIBCXX_3.4.16
GLIBCXX_3.4.17
GLIBCXX_3.4.18
GLIBCXX_3.4.19
GLIBC_2.3
GLIBC_2.2.5
GLIBC_2.14
GLIBC_2.4
GLIBC_2.3.2
GLIBCXX_DEBUG_MESSAGE_LENGTH

system('export LD_LIBRARY_PATH=/root/.conda/envs/py38/lib/:$LD_LIBRARY_PATH')

Sys.setenv("LD_LIBRARY_PATH" = "/root/.conda/envs/py38/lib")

input_shape_rgb = (img_height, img_width, 3)
data_augmentation_rgb = tf.keras.Sequential(
  [ 
    layers.RandomFlip("horizontal"),
    layers.RandomFlip("vertical"),
    layers.RandomRotation(0.5),
    layers.RandomZoom(0.5),
    layers.RandomContrast(0.5),
    RandomColorDistortion(name='random_contrast_brightness/none'),
  ]
)

# Build the model
input_shape = (img_height, img_width, 3)

model = Sequential([
  layers.Input(input_shape),
  data_augmentation_rgb,
  layers.Rescaling((1./255)),

  layers.Conv2D(16, kernel_size, padding=padding, activation='relu', strides=1, 
     data_format='channels_last'),
  layers.MaxPooling2D(),
  layers.BatchNormalization(),

  layers.Conv2D(32, kernel_size, padding=padding, activation='relu'), # best 4
  layers.MaxPooling2D(),
  layers.BatchNormalization(),

  layers.Conv2D(64, kernel_size, padding=padding, activation='relu'), # best 3
  layers.MaxPooling2D(),
  layers.BatchNormalization(),

  layers.Conv2D(128, kernel_size, padding=padding, activation='relu'), # best 3
  layers.MaxPooling2D(),
  layers.BatchNormalization(),

  layers.Flatten(),
  layers.Dense(128, activation='relu'), # best 1
  layers.Dropout(0.1),
  layers.Dense(128, activation='relu'), # best 1
  layers.Dropout(0.1),
  layers.Dense(64, activation='relu'), # best 1
  layers.Dropout(0.1),
  layers.Dense(num_classes, activation = 'softmax')
 ])

 model.compile(loss='categorical_crossentropy', optimizer='adam',metrics=metrics)
 model.summary()

model.save("./")

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-84-87d3f09f8bee> in <module>()
----> 1 model.save("./")


/usr/local/lib/python3.7/dist-packages/keras/utils/traceback_utils.py in 
 error_handler(*args, **kwargs)
 65     except Exception as e:  # pylint: disable=broad-except
 66       filtered_tb = _process_traceback_frames(e.__traceback__)
 ---> 67       raise e.with_traceback(filtered_tb) from None
 68     finally:
 69       del filtered_tb

 /usr/local/lib/python3.7/dist- 
 packages/tensorflow/python/saved_model/function_serialization.py in 
 serialize_concrete_function(concrete_function, node_ids, coder)
 66   except KeyError:
 67     raise KeyError(
 ---> 68         f"Failed to add concrete function '{concrete_function.name}' to 
 object-"
 69         f"based SavedModel as it captures tensor {capture!r} which is 
 unsupported"
 70         " or not reachable from root. "

 KeyError: "Failed to add concrete function 
 'b'__inference_sequential_46_layer_call_fn_662953'' to object-based SavedModel as it 
 captures tensor <tf.Tensor: shape=(), dtype=resource, value=<Resource Tensor>> which 
 is unsupported or not reachable from root. One reason could be that a stateful 
 object or a variable that the function depends on is not assigned to an attribute of 
 the serialized trackable object (see SaveTest.test_captures_unreachable_variable)."

import keras
from keras.datasets import cifar10
from keras.utils import to_categorical
from keras.models import Sequential
from keras.layers import Dense, Activation, Dropout, Conv2D, Flatten, MaxPooling2D
from keras.layers.normalization import BatchNormalization

(X_train, y_train), (X_test, y_test) = cifar10.load_data()

#reshape data to fit model
X_train = X_train.reshape(50000,32,32,3)
X_test = X_test.reshape(10000,32,32,3)

y_train = to_categorical(y_train)
y_test = to_categorical(y_test)


# Building the model 

#1st Convolutional Layer
model.add(Conv2D(filters=64, input_shape=(32,32,3), kernel_size=(11,11), strides=(4,4), padding='same'))
model.add(BatchNormalization())
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2,2), strides=(2,2), padding='same'))

#2nd Convolutional Layer
model.add(Conv2D(filters=224, kernel_size=(5, 5), strides=(1,1), padding='same'))
model.add(BatchNormalization())
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2,2), strides=(2,2), padding='same'))

#3rd Convolutional Layer
model.add(Conv2D(filters=288, kernel_size=(3,3), strides=(1,1), padding='same'))
model.add(BatchNormalization())
model.add(Activation('relu'))

#4th Convolutional Layer
model.add(Conv2D(filters=288, kernel_size=(3,3), strides=(1,1), padding='same'))
model.add(BatchNormalization())
model.add(Activation('relu'))

#5th Convolutional Layer
model.add(Conv2D(filters=160, kernel_size=(3,3), strides=(1,1), padding='same'))
model.add(BatchNormalization())
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2,2), strides=(2,2), padding='same'))

model.add(Flatten())

# 1st Fully Connected Layer
model.add(Dense(4096, input_shape=(32,32,3,)))
model.add(BatchNormalization())
model.add(Activation('relu'))
# Add Dropout to prevent overfitting
model.add(Dropout(0.4))

#2nd Fully Connected Layer
model.add(Dense(4096))
model.add(BatchNormalization())
model.add(Activation('relu'))
#Add Dropout
model.add(Dropout(0.4))

#3rd Fully Connected Layer
model.add(Dense(1000))
model.add(BatchNormalization())
model.add(Activation('relu'))
#Add Dropout
model.add(Dropout(0.4))

#Output Layer
model.add(Dense(10))
model.add(BatchNormalization())
model.add(Activation('softmax'))


#compile model using accuracy to measure model performance
opt = keras.optimizers.Adam(learning_rate = 0.0001)
model.compile(optimizer=opt, loss='categorical_crossentropy', 
              metrics=['accuracy'])


#train the model
model.fit(X_train, y_train, validation_data=(X_test, y_test), epochs=30)

import keras
import scipy
import numpy as np
import matplotlib.pyplot as plt
from keras.utils import to_categorical
from scipy import io

mydict = scipy.io.loadmat('Indian_pines_corrected.mat')
dataset = np.array(mydict.get('indian_pines_corrected'))


#This is creating the split between x_train and x_test from the original dataset 
# x_train after this code runs will have a shape of (121, 145, 200) 
# x_test after this code runs will have a shape of (24, 145, 200)
x_train = np.zeros((121,145,200), dtype=np.int)
x_test = np.zeros((24,145,200), dtype=np.int)    

xtemp = np.array_split(dataset, [121])
x_train = np.array(xtemp[0])
x_test = np.array(xtemp[1])

# x_train will have a shape of (17545, 200) 
# x_test will have a shape of (3480, 200)
x_train = x_train.reshape(-1, x_train.shape[-1])
x_test = x_test.reshape(-1, x_test.shape[-1])

truthDataset = scipy.io.loadmat('Indian_pines_gt.mat')
gTruth = truthDataset.get('indian_pines_gt')

#This is creating the split between Y_train and Y_test from the original dataset 
# Y_train after this code runs will have a shape of (121, 145) 
# Y_test after this code runs will have a shape of (24, 145)

Y_train = np.zeros((121,145), dtype=np.int)
Y_test = np.zeros((24,145), dtype=np.int)    

ytemp = np.array_split(gTruth, [121])
Y_train = np.array(ytemp[0])
Y_test = np.array(ytemp[1])

# Y_train will have a shape of (17545) 
# Y_test will have a shape of (3480)
Y_train = Y_train.reshape(-1)
Y_test = Y_test.reshape(-1)


#17 binary categories ranging from 0-16

#Y_train one-hot encode target column
Y_train = to_categorical(Y_train)

#Y_test one-hot encode target column
Y_test = to_categorical(Y_test, num_classes = 17)

from keras.models import Sequential
from keras.layers.normalization import BatchNormalization

2021-10-06 22:27:14.064885: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2021-10-06 22:27:14.064974: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
Traceback (most recent call last):
  File "C:\Data\breast-cancer-classification\train_model.py", line 10, in <module>
    from cancernet.cancernet import CancerNet
  File "C:\Data\breast-cancer-classification\cancernet\cancernet.py", line 2, in <module>
    from keras.layers.normalization import BatchNormalization
ImportError: cannot import name 'BatchNormalization' from 'keras.layers.normalization' (C:\Users\Catalin\AppData\Local\Programs\Python\Python39\lib\site-packages\keras\layers\normalization\__init__.py)

pip install numpy opencv-python pillow tensorflow keras imutils scikit-learn matplotlib

def action(y,x):
    #spacing between points.
    h = (x[-1] - x[0]) / (int(x.shape[0]) - 1)
    
    #fourth derivative 
    dy4 = (y[4:] - 4*y[3:-1] + 6*y[2:-2] - 4*y[1:-3] + y[:-4])/(h*h*h*h)

    return dy4

x = tf.linspace(0.0, 30, 1000)
y = tf.tanh(x)
dy4 = action(y,x)

sess = tf.compat.v1.Session()
plt.plot(sess.run(dy4))

def fourth_deriv(y, x):
    h = (x[-1] - x[0]) / (int(x.shape[0]) - 1)
    dy = (y[4:] - 4*y[3:-1] + 6*y[2:-2] - 4*y[1:-3] + y[:-4])/(h*h*h*h)
    return dy

x = np.linspace(0.0, 30, 1000)
test = fourth_deriv(np.tanh(x), x)
plt.plot(test)

@pytest.mark.usefixtures("maybe_run_functions_eagerly")
def test_save_model(speech_model: Tuple[TransducerBase, SpeechFeaturesConfig]):
    model, speech_features_config = speech_model
    speech_features_config: SpeechFeaturesConfig
    channels = 3 if speech_features_config.add_delta_deltas else 1
    num_mel_bins = speech_features_config.num_mel_bins
    enc_inputs = np.random.rand(1, 50, num_mel_bins, channels)
    dec_inputs = np.expand_dims(np.random.randint(0, 25, size=10), axis=1)
    inputs = enc_inputs, dec_inputs
    model(inputs)

    # Throws KeyError:
    # graph = tf.compat.v1.get_default_graph()
    # tensor = graph.get_tensor_by_name("77040:0")

    directory = tempfile.mkdtemp(prefix=f"{model.__class__.__name__}_")
    try:
        model.save(directory)
    finally:
        shutil.rmtree(directory)

E         AssertionError: Tried to export a function which references untracked resource Tensor("77040:0", shape=(), dtype=resource). TensorFlow objects (e.g. tf.Variable) captured by functions must be tracked by assigning them to an attribute of a tracked object or assigned to an attribute of the main object directly.
E         
E         Trackable Python objects referring to this tensor (from gc.get_referrers, limited to two hops):
E         <tf.Variable 'transformer_transducer/transducer_encoder/inputs_embedding/convolution_stack/conv2d/kernel:0' shape=(3, 3, 3, 32) dtype=float32>

model(batch)  # Build the model

tensor_name = "77040"

var_names = [var.name for var in model.trainable_weights]
weights = list(filter(lambda var: tensor_name in var, var_names))

var_names = [var.name for var in model.trainable_variables]
variables = list(filter(lambda var: tensor_name in var, var_names))

print(weights)
print(variables)

class InputsEmbedding(layers.Layer, TimeReduction):
    def __init__(self, config: InputsEmbeddingConfig, **kwargs):
        super().__init__(**kwargs)

        if config.transformations is None or not len(config.transformations):
            raise RuntimeError("No transformations provided.")

        self.config = config

        self.transformations = list()
        for transformation in self.config.transformations:
            layer_name, layer_params = list(transformation.items())[0]
            layer = _get_layer(layer_name, layer_params)
            self.transformations.append(layer)

        self.init_time_reduction_layer()

    def get_config(self):
        return self.config.dict()


def _get_layer(name: str, params: dict) -> layers.Layer:
    if name == "conv2d_stack":
        return ConvolutionStack(**params)
    elif name == "stack_frames":
        return StackFrames(**params)
    else:
        raise RuntimeError(f"Unsupported or unknown time-reduction layer {name}")

@pytest.mark.usefixtures("maybe_run_functions_eagerly")
def test_inputs_embedding_save_model():
    convolutions = [
        "filters=2, kernel_size=(3, 3), strides=(2, 1)",
        "filters=4, kernel_size=(3, 3), strides=(2, 1)",
        "filters=8, kernel_size=(3, 4), strides=(1, 1)",
    ]

    config = InputsEmbeddingConfig()
    config.transformations = [dict(conv2d_stack=dict(convolutions=convolutions)), dict(stack_frames=dict(n=2))]

    num_features = 8
    num_channels = 3

    inputs = layers.Input(shape=(None, num_features, num_channels))
    x = inputs
    x, _ = InputsEmbedding(config)(x)
    model = keras.Model(inputs=inputs, outputs=x)
    model.build(input_shape=(1, 20, num_features, num_channels))

    directory = tempfile.mkdtemp(prefix=f"{model.__class__.__name__}_")
    try:
        model.save(directory)
    finally:
        shutil.rmtree(directory)

from typing import List

import tensorflow as tf
from tensorflow.keras import layers
from tensorflow.python.keras.layers import convolutional

from speech.lab.layers import InputsRequirements
from speech.lab.models import conv_util, models_util


class ConvolutionStack(layers.Layer):
    def __init__(
        self,
        convolutions: List[str],
        kernel_regularizer: dict = None,
        bias_regularizer: dict = None,
        **kwargs
    ):
        super().__init__(**kwargs)
        self.config = dict(
            convolutions=convolutions,
            kernel_regularizer=kernel_regularizer,
            bias_regularizer=bias_regularizer
        )
        self.conv_stack_config = [eval(f"dict({convolution})") for convolution in convolutions]
        self.conv_blocks = list()

        if kernel_regularizer is not None:
            kernel_regularizer = models_util.maybe_to_regularizer(kernel_regularizer)
        if bias_regularizer is not None:
            bias_regularizer = models_util.maybe_to_regularizer(bias_regularizer)

        for block_config in self.conv_stack_config:
            block = _new_convolution_block(
                **block_config,
                kernel_regularizer=kernel_regularizer,
                bias_regularizer=bias_regularizer,
            )
            self.conv_blocks.append(block)

        self.drop_dim2 = layers.Lambda(tf.squeeze, arguments=dict(axis=-2))
        self.expand_last = layers.Lambda(tf.expand_dims, arguments=dict(axis=-1))

    @property
    def inputs_requirements(self) -> InputsRequirements:
        requirements, frame_look_back = conv_util.get_conv2d_stack_requirements(self.conv_stack_config)
        first = requirements[0]
        t_min, f_size = first["min_size"]
        t_grow, f_grow = first["grow_size"]
        return InputsRequirements(
            frame_look_back=frame_look_back,
            t_min=t_min,
            t_grow=t_grow,
            f_min=f_size,
            f_grow=f_grow,
        )

    def call(self, inputs, training=None, mask=None, **kwargs):
        """
        :param inputs:
            Tensor taking the form [batch, time, freq, channel]
        :param training:
        :param mask:
        :param kwargs:
        :return:
            Tensor taking the form [batch, time, freq, 1]
        """

        if training:
            t_min = self.inputs_requirements.t_min
            t_grow = self.inputs_requirements.t_grow
            pad = conv_util.get_padding_for_loss(tf.shape(inputs)[1], t_min=t_min, t_grow=t_grow)
            inputs = tf.pad(inputs, ((0, 0), (0, pad), (0, 0), (0, 0)))

            if mask is not None:
                mask = tf.pad(mask, ((0, 0), (0, pad)))

        f_min = self.inputs_requirements.f_min
        f_grow = self.inputs_requirements.f_grow
        assert (inputs.shape[2] - f_min) % f_grow == 0, (
            f'Inputs dimension "freq" ' f"expected to be {f_min} + n * {f_grow}  but got {inputs.shape[2]} instead."
        )

        x = inputs
        for block in self.conv_blocks:

            for layer in block:

                if mask is not None and isinstance(layer, convolutional.Conv):
                    st, _ = layer.strides
                    kt = tf.maximum(layer.kernel_size[0] - 1, 1)
                    mask = mask[:, :-kt][:, ::st]
                    mask = tf.pad(mask, ((0, 0), (0, tf.maximum(2 - layer.kernel_size[0], 0))))

                x = layer(x, training=training)

        return self.expand_last(self.drop_dim2(x)), mask

    def get_config(self):
        return self.config


def _new_convolution_block(
    filters: int,
    kernel_size: tuple,
    strides: tuple,
    use_bias: bool = False,
    use_norm: bool = True,
    kernel_regularizer=None,
    bias_regularizer=None,
    activation=None,
):
    assert strides[0] % 2 == 0 or strides[0] == 1, "Strides on the time axis must be divisible by 2 or be exactly 1."

    if activation is not None:
        activation_layer = layers.Activation(activation)
    else:
        activation_layer = layers.Lambda(lambda x: x)

    if use_norm:
        norm_layer = layers.LayerNormalization()
    else:
        norm_layer = layers.Lambda(lambda x: x)

    return (
        layers.Conv2D(
            filters=filters,
            kernel_size=kernel_size,
            strides=strides,
            use_bias=use_bias,
            kernel_regularizer=kernel_regularizer,
            bias_regularizer=bias_regularizer,
        ),
        norm_layer,
        activation_layer,
    )

Import tensorflow as tf
tf.config.list_physical_devices()

 E tensorflow/stream_executor/cuda/cuda_driver.cc:355] failed call to cuInit: CUDA_ERROR_UNKNOWN: unknown error