Fixing python module and yaml tests

.gitignore

@@ -59,4 +59,5 @@ pom.xml.versionsBackup
 konduit-serving-codegen/src/main/resources/docker/centos/aarch64/cuda/10.0/nvidia-deb/cuda-repo-l4t-10-0-local-10.0.326_1.0-1_arm64.deb
 konduit-serving-codegen/src/main/resources/docker/centos/aarch64/cuda/10.0/nvidia-deb/libcudnn7_7.6.3.28-1+cuda10.0_arm64.deb
 
-konduit-serving-core-git.properties
+konduit-serving-core-git.properties
+builds

create-all-binaries.sh

@@ -0,0 +1,31 @@
+#!/bin/bash
+
+set -euxo pipefail
+
+declare -a platforms=("windows-x86_64" "macosx-x86_64" "linux-x86_64")
+declare -a chips=("cpu" "gpu")
+declare -a spins=("minimal" "pmml" "python" "all")
+
+mkdir -p builds
+
+PROJECT_VERSION="$(mvn help:evaluate -D expression=project.version | grep -e '^[^\[]')"
+
+## now loop through the above array
+for platform in "${platforms[@]}"
+do
+ for chip in "${chips[@]}"
+ do
+ for spin in "${spins[@]}"
+ do
+ if [[ "${platform}" == 'macosx-x86_64' && "${chip}" == 'gpu' ]]; then
+ continue
+ fi
+
+ echo "Compiling for $platform | $chip | $spin"
+
+ python build_jar.py --os "${platform}" --chip "${chip}" --spin "${spin}" \
+ --target builds/konduit-serving-uberjar-"${PROJECT_VERSION}"-"${spin}"-"${platform}"-"${chip}".jar
+ done
+ done
+done
+

konduit-serving-api/src/main/java/ai/konduit/serving/pipeline/PipelineStep.java

@@ -30,33 +30,31 @@
 
 @JsonSubTypes({
  @JsonSubTypes.Type(value = PmmlStep.class, name = "PMML"),
- @JsonSubTypes.Type(value = PmmlStep.class, name = "PmmlConfig"),
+ @JsonSubTypes.Type(value = PmmlStep.class, name = "PmmlStep"),
  @JsonSubTypes.Type(value = SameDiffStep.class, name = "SAMEDIFF"),
- @JsonSubTypes.Type(value = SameDiffStep.class, name = "SameDiffConfig"),
+ @JsonSubTypes.Type(value = SameDiffStep.class, name = "SameDiffStep"),
  @JsonSubTypes.Type(value = TensorFlowStep.class, name = "TENSORFLOW"),
- @JsonSubTypes.Type(value = TensorFlowStep.class, name = "TensorFlowConfig"),
+ @JsonSubTypes.Type(value = TensorFlowStep.class, name = "TensorFlowStep"),
  @JsonSubTypes.Type(value = OnnxStep.class, name = "ONNX"),
- @JsonSubTypes.Type(value = OnnxStep.class, name = "OnnxConfig"),
+ @JsonSubTypes.Type(value = OnnxStep.class, name = "OnnxStep"),
  @JsonSubTypes.Type(value = KerasStep.class, name = "KERAS"),
- @JsonSubTypes.Type(value = KerasStep.class, name = "KerasConfig"),
+ @JsonSubTypes.Type(value = KerasStep.class, name = "KerasStep"),
  @JsonSubTypes.Type(value = Dl4jStep.class, name= "DL4J"),
- @JsonSubTypes.Type(value = Dl4jStep.class, name= "DL4JConfig"),
+ @JsonSubTypes.Type(value = Dl4jStep.class, name= "Dl4jStep"),
  @JsonSubTypes.Type(value = PythonStep.class, name = "PYTHON"),
  @JsonSubTypes.Type(value = PythonStep.class, name = "PythonStep"),
- @JsonSubTypes.Type(value = PmmlStep.class, name = "PMML"),
- @JsonSubTypes.Type(value = PmmlStep.class, name = "PmmlStep"),
  @JsonSubTypes.Type(value = TransformProcessStep.class, name = "TRANSFORM"),
  @JsonSubTypes.Type(value = TransformProcessStep.class, name = "TransformProcessStep"),
- @JsonSubTypes.Type(value = CustomPipelineStep.class, name = "CUSTOM"),
- @JsonSubTypes.Type(value = CustomPipelineStep.class, name = "CustomPipelineStep"),
  @JsonSubTypes.Type(value = ImageLoadingStep.class, name = "IMAGE"),
  @JsonSubTypes.Type(value = ImageLoadingStep.class, name = "ImageLoadingStep"),
  @JsonSubTypes.Type(value = JsonExpanderTransformStep.class, name = "JSON_EXPANDER"),
  @JsonSubTypes.Type(value = JsonExpanderTransformStep.class, name = "JsonExpanderTransformStep"),
  @JsonSubTypes.Type(value = ArrayConcatenationStep.class, name = "ARRAY_CONCAT"),
  @JsonSubTypes.Type(value = ArrayConcatenationStep.class, name = "ArrayConcatenationStep"),
  @JsonSubTypes.Type(value = WordPieceTokenizerStep.class, name = "WORDPIECE_TOKENIZER"),
- @JsonSubTypes.Type(value = WordPieceTokenizerStep.class, name = "WordPieceTokenizerStep")
+ @JsonSubTypes.Type(value = WordPieceTokenizerStep.class, name = "WordPieceTokenizerStep"),
+ @JsonSubTypes.Type(value = CustomPipelineStep.class, name = "CUSTOM"),
+ @JsonSubTypes.Type(value = CustomPipelineStep.class, name = "CustomPipelineStep")
 })
 @JsonTypeInfo(use = NAME, property = "type")
 @Deprecated

konduit-serving-codegen/src/main/java/ai/konduit/serving/codegen/pythoncodegen/CodeGen.java

@@ -24,6 +24,8 @@
 
 import ai.konduit.serving.InferenceConfiguration;
 import ai.konduit.serving.config.*;
+import ai.konduit.serving.config.metrics.ColumnDistribution;
+import ai.konduit.serving.config.metrics.MetricsConfig;
 import ai.konduit.serving.config.metrics.NoOpMetricsConfig;
 import ai.konduit.serving.config.metrics.impl.ClassificationMetricsConfig;
 import ai.konduit.serving.config.metrics.impl.MultiLabelMetricsConfig;
@@ -63,6 +65,8 @@ public static void main( String[] args ) throws Exception {
  JsonSchemaGenerator jsonSchemaGenerator = new JsonSchemaGenerator(objectMapper, JsonSchemaConfig.html5EnabledSchema());
 
  Set<Class<?>> clazzes = new LinkedHashSet<>();
+ clazzes.add(ColumnDistribution.class);
+ clazzes.add(MetricsConfig.class);
  clazzes.add(MultiLabelMetricsConfig.class);
  clazzes.add(NoOpMetricsConfig.class);
  clazzes.add(ClassificationMetricsConfig.class);

konduit-serving-core/src/main/java/ai/konduit/serving/deploy/DeployKonduitServing.java

@@ -30,12 +30,15 @@
 import io.vertx.micrometer.MicrometerMetricsOptions;
 import io.vertx.micrometer.VertxPrometheusOptions;
 import io.vertx.micrometer.backends.BackendRegistries;
+import lombok.AccessLevel;
+import lombok.NoArgsConstructor;
 import lombok.extern.slf4j.Slf4j;
 import uk.org.lidalia.sysoutslf4j.context.SysOutOverSLF4J;
 
 import java.util.concurrent.TimeUnit;
 
 @Slf4j
+@NoArgsConstructor(access = AccessLevel.PRIVATE)
 public class DeployKonduitServing {
 
  static {

konduit-serving-io/konduit-serving-camera/src/test/java/ai/konduit/serving/camera/ManualTest.java

@@ -27,7 +27,7 @@ public void manualTest() throws Exception {
  .width(w)
  .height(h)
  .outputKey("myImage")
- .build())
+  .build())
  .add(ShowImagePipelineStep.builder()
  .displayName("Image Viewer")
  .width(w)

python/cli.py

@@ -4,17 +4,19 @@
 import subprocess
 import click
 from packaging.version import parse
+from hurry.filesize import size
 
 USER_PATH = os.path.expanduser("~")
 KONDUIT_BASE_DIR = os.path.join(USER_PATH, ".konduit-serving")
 KONDUIT_SOURCE_DIR = os.path.join(KONDUIT_BASE_DIR, "source")
 KONDUIT_JAR_DIR = os.path.join(KONDUIT_BASE_DIR, "jar")
 KONDUIT_JAR_PATH = os.path.join(KONDUIT_JAR_DIR, "konduit.jar")
 
+INCOMPATIBLE_COMPILATION_TAGS = ["cli_base", "cli_base_2", "cli_base_3", "cli_base_4"]
 DOWNLOAD_TAG = "cli_base"
 
 LAST_COMPATIBLE_KONDUIT_VERSION = "0.1.0-SNAPSHOT"
-DEFAULT_KONDUIT_TAG = "cli_base_2"
+DEFAULT_KONDUIT_TAG = "cli_base_4"
 KONDUIT_JAR_URL_FORMAT = "https://github.com/KonduitAI/konduit-serving/releases/download/" \
  "{tag}/konduit-serving-uberjar-{version}-{spin}-{platform}-{chip}.jar"
 
@@ -54,7 +56,7 @@ def download_if_required(url, save_path):
  print("The required CLI binary has already been downloaded.")
  return
  else:
- print("Downloading command line binaries")
+ print("Downloading command line binaries from " + url)
 
  with open(save_path, 'wb') as f:
  if total is None:
@@ -66,7 +68,8 @@ def download_if_required(url, save_path):
  downloaded += len(data)
  f.write(data)
  done = int(50 * downloaded / total)
- sys.stdout.write('\r[{}{}]'.format('█' * done, '.' * (50 - done)))
+ sys.stdout.write('\r[{}{}]'.format('█' * done, '.' * (50 - done)) +
+ (" ({}/{})".format(size(downloaded), size(total))))
  sys.stdout.flush()
  sys.stdout.write('\n')
 
@@ -154,7 +157,9 @@ def get_jar_url(platform, version, spin, chip):
  chip=chip)
 
 
-git_tags = get_git_tags()
+git_tags = set(get_git_tags()).difference(INCOMPATIBLE_COMPILATION_TAGS)
+if len(git_tags) == 0:
+ git_tags = [DEFAULT_KONDUIT_TAG]
 DEFAULT_KONDUIT_TAG = git_tags[0] # Assuming the first one in the response is the most recent one
 
 
@@ -230,4 +235,4 @@ def cli():
  subprocess.call(
  arguments,
  shell=sys.platform.startswith("win")
- )
+ )

python/konduit/__init__.py

@@ -1,10 +1,10 @@
 import os
 
 USER_PATH = os.path.expanduser("~")
-KONDUIT_BASE_DIR = os.path.join(USER_PATH, ".konduit")
-KONDUIT_DIR = os.path.join(KONDUIT_BASE_DIR, "konduit-serving")
+KONDUIT_BASE_DIR = os.path.join(USER_PATH, ".konduit-serving")
+KONDUIT_JAR_DIR = os.path.join(KONDUIT_BASE_DIR, "jar")
 
-jar = os.getenv("KONDUIT_JAR_PATH", os.path.join(KONDUIT_DIR, "konduit.jar"))
+jar = os.getenv("KONDUIT_JAR_PATH", os.path.join(KONDUIT_JAR_DIR, "konduit.jar"))
 
 try:
  import pydl4j

python/konduit/base_inference.py

@@ -2,6 +2,133 @@
 from konduit.json_utils import empty_type_dict, DictWrapper, ListWrapper
 
 
+class ColumnDistribution(object):
+
+ _normalizerType_enum = enum.Enum(
+ "_normalizerType_enum",
+ "STANDARDIZE MIN_MAX IMAGE_MIN_MAX IMAGE_VGG16 MULTI_STANDARDIZE MULTI_MIN_MAX MULTI_HYBRID CUSTOM",
+ module=__name__,
+ )
+ _types_map = {
+ "mean": {"type": float, "subtype": None},
+ "min": {"type": float, "subtype": None},
+ "max": {"type": float, "subtype": None},
+ "standardDeviation": {"type": float, "subtype": None},
+ "normalizerType": {"type": str, "subtype": None},
+ }
+ _formats_map = {}
+
+ def __init__(
+ self,
+ mean=None,
+ min=None,
+ max=None,
+ standard_deviation=None,
+ normalizer_type=None,
+ ):
+ self.__mean = mean
+ self.__min = min
+ self.__max = max
+ self.__standard_deviation = standard_deviation
+ self.__normalizer_type = normalizer_type
+
+ def _get_mean(self):
+ return self.__mean
+
+ def _set_mean(self, value):
+ if not isinstance(value, float):
+ raise TypeError("mean must be float")
+ self.__mean = value
+
+ mean = property(_get_mean, _set_mean)
+
+ def _get_min(self):
+ return self.__min
+
+ def _set_min(self, value):
+ if not isinstance(value, float):
+ raise TypeError("min must be float")
+ self.__min = value
+
+ min = property(_get_min, _set_min)
+
+ def _get_max(self):
+ return self.__max
+
+ def _set_max(self, value):
+ if not isinstance(value, float):
+ raise TypeError("max must be float")
+ self.__max = value
+
+ max = property(_get_max, _set_max)
+
+ def _get_standard_deviation(self):
+ return self.__standard_deviation
+
+ def _set_standard_deviation(self, value):
+ if not isinstance(value, float):
+ raise TypeError("standardDeviation must be float")
+ self.__standard_deviation = value
+
+ standard_deviation = property(_get_standard_deviation, _set_standard_deviation)
+
+ def _get_normalizer_type(self):
+ return self.__normalizer_type
+
+ def _set_normalizer_type(self, value):
+ if not isinstance(value, str):
+ raise TypeError("normalizerType must be str")
+ if value in self._normalizerType_enum.__members__:
+ self.__type = value
+ else:
+ raise ValueError("Value {} not in _normalizerType_enum list".format(value))
+
+ normalizer_type = property(_get_normalizer_type, _set_normalizer_type)
+
+ def as_dict(self):
+ d = empty_type_dict(self)
+ if self.__mean is not None:
+ d["mean"] = (
+ self.__mean.as_dict()
+ if hasattr(self.__mean, "as_dict")
+ else self.__mean
+ )
+ if self.__min is not None:
+ d["min"] = (
+ self.__min.as_dict() if hasattr(self.__min, "as_dict") else self.__min
+ )
+ if self.__max is not None:
+ d["max"] = (
+ self.__max.as_dict() if hasattr(self.__max, "as_dict") else self.__max
+ )
+ if self.__standard_deviation is not None:
+ d["standardDeviation"] = (
+ self.__standard_deviation.as_dict()
+ if hasattr(self.__standard_deviation, "as_dict")
+ else self.__standard_deviation
+ )
+ if self.__normalizer_type is not None:
+ d["normalizerType"] = (
+ self.__normalizer_type.as_dict()
+ if hasattr(self.__normalizer_type, "as_dict")
+ else self.__normalizer_type
+ )
+ return d
+
+
+class MetricsConfig(object):
+
+ _types_map = {}
+ _formats_map = {}
+
+ def __init__(self):
+ pass
+
+ def as_dict(self):
+ d = empty_type_dict(self)
+ return d
+
+
 class MultiLabelMetricsConfig(object):
 
  _types_map = {
@@ -888,11 +1015,11 @@ class ServingConfig(object):
  def __init__(
  self,
  http_port=None,
- listen_host=None,
+ listen_host="localhost",
  output_data_format="NUMPY",
  uploads_directory="file-uploads/",
- log_timings=None,
- create_logging_endpoints=None,
+ log_timings=False,
+ create_logging_endpoints=False,
  metrics_configurations=None,
  metric_types=None,
  ):

python/konduit/json_utils.py

@@ -52,27 +52,27 @@ def _ensure_serializable(input_config):
 def config_to_dict_with_type(inference_config):
  """
  Converts an inference configuration to a Python dictionary
- with '@type' key.
+ with 'type' key.
 
  :param inference_config: InferenceConfig object
  :return: Python dict
  """
  has_as_dict_attribute(inference_config)
  _ensure_serializable(inference_config)
  input_dict = inference_config.as_dict()
- input_dict["@type"] = inference_config.__class__.__name__
+ input_dict["type"] = inference_config.__class__.__name__
  return input_dict
 
 
 def empty_type_dict(input_object):
  """Generates an otherwise empty Python dict with the correct
- "@type" key from Java.
+ "type" key from Java.
 
  :param input_class: arbitrary instance of a Python class
  :return:
  """
  d = dict()
- d["@type"] = input_object.__class__.__name__
+ d["type"] = input_object.__class__.__name__
  return d
 
 

python/konduit/load.py

@@ -132,7 +132,7 @@ def server_from_file(file_path, start_server=False, use_yaml=True):
 
  step_data = data.get("steps", None)
  steps = []
- for step_config in step_data.values():
+ for step_config in step_data:
  steps.append(get_step(step_config))
 
  server = Server(
@@ -211,8 +211,8 @@ def get_python_step(step_config):
  """
 
  python_step = PythonStep()
- for key, python_config in step_config:
- python_step.step(key, PythonConfig(**python_config))
+ for key, config in step_config["python_configs"].items():
+ python_step.step(python_config=PythonConfig(**config), input_name=key)
 
  return python_step