diff options
author | Lester Solbakken <lesters@users.noreply.github.com> | 2021-05-19 14:26:28 +0200 |
---|---|---|
committer | GitHub <noreply@github.com> | 2021-05-19 14:26:28 +0200 |
commit | 97080252fac0ba45b58f9d0efb56603da518428f (patch) | |
tree | 75255be3447ca5272f1bac08693d15afb944c6cc | |
parent | 390a26e1a42486fefedef5468c86a781d1d833d1 (diff) |
Revert "Add ONNX-RT evaluator to model-integration module"
25 files changed, 0 insertions, 697 deletions
diff --git a/cloud-tenant-base-dependencies-enforcer/pom.xml b/cloud-tenant-base-dependencies-enforcer/pom.xml index 16045d5dc75..ae833f68d9b 100644 --- a/cloud-tenant-base-dependencies-enforcer/pom.xml +++ b/cloud-tenant-base-dependencies-enforcer/pom.xml @@ -34,7 +34,6 @@ <jetty-alpn.version>1.1.3.v20160715</jetty-alpn.version> <junit5.version>5.7.0</junit5.version> <junit5.platform.version>1.7.0</junit5.platform.version> - <onnxruntime.version>1.7.0</onnxruntime.version> <org.lz4.version>1.7.1</org.lz4.version> <org.json.version>20090211</org.json.version><!-- TODO Vespa 8: remove as provided dependency --> <slf4j.version>1.7.30</slf4j.version> @@ -220,7 +219,6 @@ <include>com.google.protobuf:protobuf-java:3.7.0:jar:test</include> <include>com.ibm.icu:icu4j:57.1:jar:test</include> <include>com.intellij:annotations:12.0:jar:test</include> - <include>com.microsoft.onnxruntime:onnxruntime:[${onnxruntime.version}]:jar:test</include> <include>com.optimaize.languagedetector:language-detector:0.6:jar:test</include> <include>com.thaiopensource:jing:20091111:jar:test</include> <include>com.yahoo.athenz:athenz-auth-core:[${athenz.version}]:jar:test</include> diff --git a/model-integration/pom.xml b/model-integration/pom.xml index dc3154c5c41..536d3578f8c 100644 --- a/model-integration/pom.xml +++ b/model-integration/pom.xml @@ -53,10 +53,6 @@ </dependency> <dependency> - <groupId>com.microsoft.onnxruntime</groupId> - <artifactId>onnxruntime</artifactId> - </dependency> - <dependency> <groupId>com.google.protobuf</groupId> <artifactId>protobuf-java</artifactId> </dependency> diff --git a/model-integration/src/main/java/ai/vespa/modelintegration/evaluator/OnnxEvaluator.java b/model-integration/src/main/java/ai/vespa/modelintegration/evaluator/OnnxEvaluator.java deleted file mode 100644 index 59ad20b7714..00000000000 --- a/model-integration/src/main/java/ai/vespa/modelintegration/evaluator/OnnxEvaluator.java +++ /dev/null @@ -1,79 +0,0 @@ -// Copyright Verizon Media. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. - -package ai.vespa.modelintegration.evaluator; - -import ai.onnxruntime.OnnxTensor; -import ai.onnxruntime.OnnxValue; -import ai.onnxruntime.OrtEnvironment; -import ai.onnxruntime.OrtException; -import ai.onnxruntime.OrtSession; -import com.yahoo.tensor.Tensor; -import com.yahoo.tensor.TensorType; - -import java.util.Collections; -import java.util.HashMap; -import java.util.Map; - - -/** - * Evaluates an ONNX Model by deferring to ONNX Runtime. - * - * @author lesters - */ -public class OnnxEvaluator { - - private final OrtEnvironment environment; - private final OrtSession session; - - public OnnxEvaluator(String modelPath) { - try { - environment = OrtEnvironment.getEnvironment(); - session = environment.createSession(modelPath, new OrtSession.SessionOptions()); - } catch (OrtException e) { - throw new RuntimeException("ONNX Runtime exception", e); - } - } - - public Tensor evaluate(Map<String, Tensor> inputs, String output) { - try { - Map<String, OnnxTensor> onnxInputs = TensorConverter.toOnnxTensors(inputs, environment, session); - try (OrtSession.Result result = session.run(onnxInputs, Collections.singleton(output))) { - return TensorConverter.toVespaTensor(result.get(0)); - } - } catch (OrtException e) { - throw new RuntimeException("ONNX Runtime exception", e); - } - } - - public Map<String, Tensor> evaluate(Map<String, Tensor> inputs) { - try { - Map<String, OnnxTensor> onnxInputs = TensorConverter.toOnnxTensors(inputs, environment, session); - Map<String, Tensor> outputs = new HashMap<>(); - try (OrtSession.Result result = session.run(onnxInputs)) { - for (Map.Entry<String, OnnxValue> output : result) { - outputs.put(output.getKey(), TensorConverter.toVespaTensor(output.getValue())); - } - return outputs; - } - } catch (OrtException e) { - throw new RuntimeException("ONNX Runtime exception", e); - } - } - - public Map<String, TensorType> getInputInfo() { - try { - return TensorConverter.toVespaTypes(session.getInputInfo()); - } catch (OrtException e) { - throw new RuntimeException("ONNX Runtime exception", e); - } - } - - public Map<String, TensorType> getOutputInfo() { - try { - return TensorConverter.toVespaTypes(session.getOutputInfo()); - } catch (OrtException e) { - throw new RuntimeException("ONNX Runtime exception", e); - } - } - -} diff --git a/model-integration/src/main/java/ai/vespa/modelintegration/evaluator/TensorConverter.java b/model-integration/src/main/java/ai/vespa/modelintegration/evaluator/TensorConverter.java deleted file mode 100644 index c1f973300d6..00000000000 --- a/model-integration/src/main/java/ai/vespa/modelintegration/evaluator/TensorConverter.java +++ /dev/null @@ -1,181 +0,0 @@ -// Copyright Verizon Media. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. - -package ai.vespa.modelintegration.evaluator; - -import ai.onnxruntime.NodeInfo; -import ai.onnxruntime.OnnxJavaType; -import ai.onnxruntime.OnnxTensor; -import ai.onnxruntime.OnnxValue; -import ai.onnxruntime.OrtEnvironment; -import ai.onnxruntime.OrtException; -import ai.onnxruntime.OrtSession; -import ai.onnxruntime.TensorInfo; -import ai.onnxruntime.ValueInfo; -import com.yahoo.tensor.DimensionSizes; -import com.yahoo.tensor.IndexedTensor; -import com.yahoo.tensor.Tensor; -import com.yahoo.tensor.TensorType; - -import java.nio.ByteBuffer; -import java.nio.ByteOrder; -import java.nio.DoubleBuffer; -import java.nio.FloatBuffer; -import java.nio.IntBuffer; -import java.nio.LongBuffer; -import java.nio.ShortBuffer; -import java.util.HashMap; -import java.util.Map; -import java.util.stream.Collectors; - - -/** - * @author lesters - */ -class TensorConverter { - - static Map<String, OnnxTensor> toOnnxTensors(Map<String, Tensor> tensorMap, OrtEnvironment env, OrtSession session) - throws OrtException - { - Map<String, OnnxTensor> result = new HashMap<>(); - for (String name : tensorMap.keySet()) { - Tensor vespaTensor = tensorMap.get(name); - TensorInfo onnxTensorInfo = toTensorInfo(session.getInputInfo().get(name).getInfo()); - OnnxTensor onnxTensor = toOnnxTensor(vespaTensor, onnxTensorInfo, env); - result.put(name, onnxTensor); - } - return result; - } - - static OnnxTensor toOnnxTensor(Tensor vespaTensor, TensorInfo onnxTensorInfo, OrtEnvironment environment) - throws OrtException - { - if ( ! (vespaTensor instanceof IndexedTensor)) { - throw new IllegalArgumentException("OnnxEvaluator currently only supports tensors with indexed dimensions"); - } - IndexedTensor tensor = (IndexedTensor) vespaTensor; - - ByteBuffer buffer = ByteBuffer.allocateDirect((int)tensor.size() * onnxTensorInfo.type.size).order(ByteOrder.nativeOrder()); - if (onnxTensorInfo.type == OnnxJavaType.FLOAT) { - for (int i = 0; i < tensor.size(); i++) - buffer.putFloat(tensor.getFloat(i)); - return OnnxTensor.createTensor(environment, buffer.rewind().asFloatBuffer(), tensor.shape()); - } - if (onnxTensorInfo.type == OnnxJavaType.DOUBLE) { - for (int i = 0; i < tensor.size(); i++) - buffer.putDouble(tensor.get(i)); - return OnnxTensor.createTensor(environment, buffer.rewind().asDoubleBuffer(), tensor.shape()); - } - if (onnxTensorInfo.type == OnnxJavaType.INT8) { - for (int i = 0; i < tensor.size(); i++) - buffer.put((byte) tensor.get(i)); - return OnnxTensor.createTensor(environment, buffer.rewind(), tensor.shape()); - } - if (onnxTensorInfo.type == OnnxJavaType.INT16) { - for (int i = 0; i < tensor.size(); i++) - buffer.putShort((short) tensor.get(i)); - return OnnxTensor.createTensor(environment, buffer.rewind().asShortBuffer(), tensor.shape()); - } - if (onnxTensorInfo.type == OnnxJavaType.INT32) { - for (int i = 0; i < tensor.size(); i++) - buffer.putInt((int) tensor.get(i)); - return OnnxTensor.createTensor(environment, buffer.rewind().asIntBuffer(), tensor.shape()); - } - if (onnxTensorInfo.type == OnnxJavaType.INT64) { - for (int i = 0; i < tensor.size(); i++) - buffer.putLong((long) tensor.get(i)); - return OnnxTensor.createTensor(environment, buffer.rewind().asLongBuffer(), tensor.shape()); - } - throw new IllegalArgumentException("OnnxEvaluator does not currently support value type " + onnxTensorInfo.type); - } - - static Tensor toVespaTensor(OnnxValue onnxValue) { - if ( ! (onnxValue instanceof OnnxTensor)) { - throw new IllegalArgumentException("ONNX value is not a tensor: maps and sequences are not yet supported"); - } - OnnxTensor onnxTensor = (OnnxTensor) onnxValue; - TensorInfo tensorInfo = onnxTensor.getInfo(); - - TensorType type = toVespaType(onnxTensor.getInfo()); - DimensionSizes sizes = sizesFromType(type); - - IndexedTensor.BoundBuilder builder = (IndexedTensor.BoundBuilder) Tensor.Builder.of(type, sizes); - if (tensorInfo.type == OnnxJavaType.FLOAT) { - FloatBuffer buffer = onnxTensor.getFloatBuffer(); - for (long i = 0; i < sizes.totalSize(); i++) - builder.cellByDirectIndex(i, buffer.get()); - } - else if (tensorInfo.type == OnnxJavaType.DOUBLE) { - DoubleBuffer buffer = onnxTensor.getDoubleBuffer(); - for (long i = 0; i < sizes.totalSize(); i++) - builder.cellByDirectIndex(i, buffer.get()); - } - else if (tensorInfo.type == OnnxJavaType.INT8) { - ByteBuffer buffer = onnxTensor.getByteBuffer(); - for (long i = 0; i < sizes.totalSize(); i++) - builder.cellByDirectIndex(i, buffer.get()); - } - else if (tensorInfo.type == OnnxJavaType.INT16) { - ShortBuffer buffer = onnxTensor.getShortBuffer(); - for (long i = 0; i < sizes.totalSize(); i++) - builder.cellByDirectIndex(i, buffer.get()); - } - else if (tensorInfo.type == OnnxJavaType.INT32) { - IntBuffer buffer = onnxTensor.getIntBuffer(); - for (long i = 0; i < sizes.totalSize(); i++) - builder.cellByDirectIndex(i, buffer.get()); - } - else if (tensorInfo.type == OnnxJavaType.INT64) { - LongBuffer buffer = onnxTensor.getLongBuffer(); - for (long i = 0; i < sizes.totalSize(); i++) - builder.cellByDirectIndex(i, buffer.get()); - } - else { - throw new IllegalArgumentException("OnnxEvaluator does not currently support value type " + onnxTensor.getInfo().type); - } - return builder.build(); - } - - static private DimensionSizes sizesFromType(TensorType type) { - DimensionSizes.Builder builder = new DimensionSizes.Builder(type.dimensions().size()); - for (int i = 0; i < type.dimensions().size(); i++) - builder.set(i, type.dimensions().get(i).size().get()); - return builder.build(); - } - - static Map<String, TensorType> toVespaTypes(Map<String, NodeInfo> infoMap) { - return infoMap.entrySet().stream().collect(Collectors.toMap(e -> e.getKey(), e -> toVespaType(e.getValue().getInfo()))); - } - - static TensorType toVespaType(ValueInfo valueInfo) { - TensorInfo tensorInfo = toTensorInfo(valueInfo); - TensorType.Builder builder = new TensorType.Builder(toVespaValueType(tensorInfo.onnxType)); - long[] shape = tensorInfo.getShape(); - for (int i = 0; i < shape.length; ++i) { - long dimSize = shape[i]; - String dimName = "d" + i; // standard naming convention - if (dimSize > 0) - builder.indexed(dimName, dimSize); - else - builder.indexed(dimName); // unbound dimension for dim size -1 - } - return builder.build(); - } - - static private TensorType.Value toVespaValueType(TensorInfo.OnnxTensorType onnxType) { - switch (onnxType) { - case ONNX_TENSOR_ELEMENT_DATA_TYPE_INT8: return TensorType.Value.INT8; - case ONNX_TENSOR_ELEMENT_DATA_TYPE_BFLOAT16: return TensorType.Value.BFLOAT16; - case ONNX_TENSOR_ELEMENT_DATA_TYPE_FLOAT: return TensorType.Value.FLOAT; - case ONNX_TENSOR_ELEMENT_DATA_TYPE_DOUBLE: return TensorType.Value.DOUBLE; - } - return TensorType.Value.DOUBLE; - } - - static private TensorInfo toTensorInfo(ValueInfo valueInfo) { - if ( ! (valueInfo instanceof TensorInfo)) { - throw new IllegalArgumentException("ONNX value is not a tensor: maps and sequences are not yet supported"); - } - return (TensorInfo) valueInfo; - } - -} diff --git a/model-integration/src/main/java/ai/vespa/modelintegration/evaluator/package-info.java b/model-integration/src/main/java/ai/vespa/modelintegration/evaluator/package-info.java deleted file mode 100644 index e44ea96c534..00000000000 --- a/model-integration/src/main/java/ai/vespa/modelintegration/evaluator/package-info.java +++ /dev/null @@ -1,5 +0,0 @@ -// Copyright Verizon Media. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. -@ExportPackage -package ai.vespa.modelintegration.evaluator; - -import com.yahoo.osgi.annotation.ExportPackage;
\ No newline at end of file diff --git a/model-integration/src/test/java/ai/vespa/modelintegration/evaluator/OnnxEvaluatorTest.java b/model-integration/src/test/java/ai/vespa/modelintegration/evaluator/OnnxEvaluatorTest.java deleted file mode 100644 index 4b42e18d75e..00000000000 --- a/model-integration/src/test/java/ai/vespa/modelintegration/evaluator/OnnxEvaluatorTest.java +++ /dev/null @@ -1,93 +0,0 @@ -// Copyright Verizon Media. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. - -package ai.vespa.modelintegration.evaluator; - -import com.yahoo.tensor.Tensor; -import com.yahoo.tensor.TensorType; -import org.junit.Test; - -import java.util.HashMap; -import java.util.Map; - -import static org.junit.Assert.assertEquals; - -/** - * @author lesters - */ -public class OnnxEvaluatorTest { - - @Test - public void testSimpleMoodel() { - OnnxEvaluator evaluator = new OnnxEvaluator("src/test/models/onnx/simple/simple.onnx"); - - // Input types - Map<String, TensorType> inputTypes = evaluator.getInputInfo(); - assertEquals(inputTypes.get("query_tensor"), TensorType.fromSpec("tensor<float>(d0[1],d1[4])")); - assertEquals(inputTypes.get("attribute_tensor"), TensorType.fromSpec("tensor<float>(d0[4],d1[1])")); - assertEquals(inputTypes.get("bias_tensor"), TensorType.fromSpec("tensor<float>(d0[1],d1[1])")); - - // Output types - Map<String, TensorType> outputTypes = evaluator.getOutputInfo(); - assertEquals(outputTypes.get("output"), TensorType.fromSpec("tensor<float>(d0[1],d1[1])")); - - // Evaluation - Map<String, Tensor> inputs = new HashMap<>(); - inputs.put("query_tensor", Tensor.from("tensor(d0[1],d1[4]):[0.1, 0.2, 0.3, 0.4]")); - inputs.put("attribute_tensor", Tensor.from("tensor(d0[4],d1[1]):[0.1, 0.2, 0.3, 0.4]")); - inputs.put("bias_tensor", Tensor.from("tensor(d0[1],d1[1]):[1.0]")); - - assertEquals(evaluator.evaluate(inputs).get("output"), Tensor.from("tensor(d0[1],d1[1]):[1.3]")); - assertEquals(evaluator.evaluate(inputs, "output"), Tensor.from("tensor(d0[1],d1[1]):[1.3]")); - } - - @Test - public void testBatchDimension() { - OnnxEvaluator evaluator = new OnnxEvaluator("src/test/models/onnx/pytorch/one_layer.onnx"); - - // Input types - Map<String, TensorType> inputTypes = evaluator.getInputInfo(); - assertEquals(inputTypes.get("input"), TensorType.fromSpec("tensor<float>(d0[],d1[3])")); - - // Output types - Map<String, TensorType> outputTypes = evaluator.getOutputInfo(); - assertEquals(outputTypes.get("output"), TensorType.fromSpec("tensor<float>(d0[],d1[1])")); - - // Evaluation - Map<String, Tensor> inputs = new HashMap<>(); - inputs.put("input", Tensor.from("tensor<float>(d0[2],d1[3]):[[0.1, 0.2, 0.3],[0.4,0.5,0.6]]")); - assertEquals(evaluator.evaluate(inputs, "output"), Tensor.from("tensor<float>(d0[2],d1[1]):[0.6393113,0.67574286]")); - } - - @Test - public void testMatMul() { - String expected = "tensor<float>(d0[2],d1[4]):[38,44,50,56,83,98,113,128]"; - String input1 = "tensor<float>(d0[2],d1[3]):[1,2,3,4,5,6]"; - String input2 = "tensor<float>(d0[3],d1[4]):[1,2,3,4,5,6,7,8,9,10,11,12]"; - assertEvaluate("simple/matmul.onnx", expected, input1, input2); - } - - @Test - public void testTypes() { - assertEvaluate("add_double.onnx", "tensor(d0[1]):[3]", "tensor(d0[1]):[1]", "tensor(d0[1]):[2]"); - assertEvaluate("add_float.onnx", "tensor<float>(d0[1]):[3]", "tensor<float>(d0[1]):[1]", "tensor<float>(d0[1]):[2]"); - assertEvaluate("add_int64.onnx", "tensor<double>(d0[1]):[3]", "tensor<double>(d0[1]):[1]", "tensor<double>(d0[1]):[2]"); - assertEvaluate("cast_int8_float.onnx", "tensor<float>(d0[1]):[-128]", "tensor<int8>(d0[1]):[128]"); - assertEvaluate("cast_float_int8.onnx", "tensor<int8>(d0[1]):[-1]", "tensor<float>(d0[1]):[255]"); - - // ONNX Runtime 1.7.0 does not support much of bfloat16 yet - // assertEvaluate("cast_bfloat16_float.onnx", "tensor<float>(d0[1]):[1]", "tensor<bfloat16>(d0[1]):[1]"); - } - - private void assertEvaluate(String model, String output, String... input) { - OnnxEvaluator evaluator = new OnnxEvaluator("src/test/models/onnx/" + model); - Map<String, Tensor> inputs = new HashMap<>(); - for (int i = 0; i < input.length; ++i) { - inputs.put("input" + (i+1), Tensor.from(input[i])); - } - Tensor expected = Tensor.from(output); - Tensor result = evaluator.evaluate(inputs, "output"); - assertEquals(expected, result); - assertEquals(expected.type().valueType(), result.type().valueType()); - } - -} diff --git a/model-integration/src/test/models/onnx/add_double.onnx b/model-integration/src/test/models/onnx/add_double.onnx deleted file mode 100644 index 9264d1eb9f9..00000000000 --- a/model-integration/src/test/models/onnx/add_double.onnx +++ /dev/null @@ -1,16 +0,0 @@ -
add_double.py:f - -input1 -input2output"AddaddZ -input1 - - -Z -input2 - - -b -output - - -B
\ No newline at end of file diff --git a/model-integration/src/test/models/onnx/add_double.py b/model-integration/src/test/models/onnx/add_double.py deleted file mode 100755 index fa9aa48f4b2..00000000000 --- a/model-integration/src/test/models/onnx/add_double.py +++ /dev/null @@ -1,27 +0,0 @@ -# Copyright Verizon Media. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. - -import onnx -from onnx import helper, TensorProto - -INPUT_1 = helper.make_tensor_value_info('input1', TensorProto.DOUBLE, [1]) -INPUT_2 = helper.make_tensor_value_info('input2', TensorProto.DOUBLE, [1]) -OUTPUT = helper.make_tensor_value_info('output', TensorProto.DOUBLE, [1]) - -nodes = [ - helper.make_node( - 'Add', - ['input1', 'input2'], - ['output'], - ), -] -graph_def = helper.make_graph( - nodes, - 'add', - [ - INPUT_1, - INPUT_2 - ], - [OUTPUT], -) -model_def = helper.make_model(graph_def, producer_name='add_double.py', opset_imports=[onnx.OperatorSetIdProto(version=12)]) -onnx.save(model_def, 'add_double.onnx') diff --git a/model-integration/src/test/models/onnx/add_float.onnx b/model-integration/src/test/models/onnx/add_float.onnx deleted file mode 100644 index 0e3ad8f900c..00000000000 --- a/model-integration/src/test/models/onnx/add_float.onnx +++ /dev/null @@ -1,16 +0,0 @@ -add_float.py:f - -input1 -input2output"AddaddZ -input1 - - -Z -input2 - - -b -output - - -B
\ No newline at end of file diff --git a/model-integration/src/test/models/onnx/add_float.py b/model-integration/src/test/models/onnx/add_float.py deleted file mode 100755 index e18b2c46d9d..00000000000 --- a/model-integration/src/test/models/onnx/add_float.py +++ /dev/null @@ -1,27 +0,0 @@ -# Copyright Verizon Media. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. - -import onnx -from onnx import helper, TensorProto - -INPUT_1 = helper.make_tensor_value_info('input1', TensorProto.FLOAT, [1]) -INPUT_2 = helper.make_tensor_value_info('input2', TensorProto.FLOAT, [1]) -OUTPUT = helper.make_tensor_value_info('output', TensorProto.FLOAT, [1]) - -nodes = [ - helper.make_node( - 'Add', - ['input1', 'input2'], - ['output'], - ), -] -graph_def = helper.make_graph( - nodes, - 'add', - [ - INPUT_1, - INPUT_2 - ], - [OUTPUT], -) -model_def = helper.make_model(graph_def, producer_name='add_float.py', opset_imports=[onnx.OperatorSetIdProto(version=12)]) -onnx.save(model_def, 'add_float.onnx') diff --git a/model-integration/src/test/models/onnx/add_int64.onnx b/model-integration/src/test/models/onnx/add_int64.onnx deleted file mode 100644 index 7b3a9ec6b95..00000000000 --- a/model-integration/src/test/models/onnx/add_int64.onnx +++ /dev/null @@ -1,16 +0,0 @@ -add_int64.py:f - -input1 -input2output"AddaddZ -input1 - - -Z -input2 - - -b -output - - -B
\ No newline at end of file diff --git a/model-integration/src/test/models/onnx/add_int64.py b/model-integration/src/test/models/onnx/add_int64.py deleted file mode 100755 index 87908e292a2..00000000000 --- a/model-integration/src/test/models/onnx/add_int64.py +++ /dev/null @@ -1,27 +0,0 @@ -# Copyright Verizon Media. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. - -import onnx -from onnx import helper, TensorProto - -INPUT_1 = helper.make_tensor_value_info('input1', TensorProto.INT64, [1]) -INPUT_2 = helper.make_tensor_value_info('input2', TensorProto.INT64, [1]) -OUTPUT = helper.make_tensor_value_info('output', TensorProto.INT64, [1]) - -nodes = [ - helper.make_node( - 'Add', - ['input1', 'input2'], - ['output'], - ), -] -graph_def = helper.make_graph( - nodes, - 'add', - [ - INPUT_1, - INPUT_2 - ], - [OUTPUT], -) -model_def = helper.make_model(graph_def, producer_name='add_int64.py', opset_imports=[onnx.OperatorSetIdProto(version=12)]) -onnx.save(model_def, 'add_int64.onnx') diff --git a/model-integration/src/test/models/onnx/cast_bfloat16_float.onnx b/model-integration/src/test/models/onnx/cast_bfloat16_float.onnx deleted file mode 100644 index cb19592abf4..00000000000 --- a/model-integration/src/test/models/onnx/cast_bfloat16_float.onnx +++ /dev/null @@ -1,12 +0,0 @@ -cast_bfloat16_float.py:U -! -input1output"Cast* -to castZ -input1 - - -b -output - - -B
\ No newline at end of file diff --git a/model-integration/src/test/models/onnx/cast_bfloat16_float.py b/model-integration/src/test/models/onnx/cast_bfloat16_float.py deleted file mode 100755 index 14b05347262..00000000000 --- a/model-integration/src/test/models/onnx/cast_bfloat16_float.py +++ /dev/null @@ -1,24 +0,0 @@ -# Copyright Verizon Media. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. - -import onnx -from onnx import helper, TensorProto - -INPUT_1 = helper.make_tensor_value_info('input1', TensorProto.BFLOAT16, [1]) -OUTPUT = helper.make_tensor_value_info('output', TensorProto.FLOAT, [1]) - -nodes = [ - helper.make_node( - 'Cast', - ['input1'], - ['output'], - to=TensorProto.FLOAT - ), -] -graph_def = helper.make_graph( - nodes, - 'cast', - [INPUT_1], - [OUTPUT], -) -model_def = helper.make_model(graph_def, producer_name='cast_bfloat16_float.py', opset_imports=[onnx.OperatorSetIdProto(version=12)]) -onnx.save(model_def, 'cast_bfloat16_float.onnx') diff --git a/model-integration/src/test/models/onnx/cast_float_int8.onnx b/model-integration/src/test/models/onnx/cast_float_int8.onnx deleted file mode 100644 index c30b023dd68..00000000000 --- a/model-integration/src/test/models/onnx/cast_float_int8.onnx +++ /dev/null @@ -1,12 +0,0 @@ -cast_float_int8.py:U -! -input1output"Cast* -to castZ -input1 - - -b -output - - -B
\ No newline at end of file diff --git a/model-integration/src/test/models/onnx/cast_float_int8.py b/model-integration/src/test/models/onnx/cast_float_int8.py deleted file mode 100755 index bdc0850d033..00000000000 --- a/model-integration/src/test/models/onnx/cast_float_int8.py +++ /dev/null @@ -1,24 +0,0 @@ -# Copyright Verizon Media. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. - -import onnx -from onnx import helper, TensorProto - -INPUT_1 = helper.make_tensor_value_info('input1', TensorProto.FLOAT, [1]) -OUTPUT = helper.make_tensor_value_info('output', TensorProto.INT8, [1]) - -nodes = [ - helper.make_node( - 'Cast', - ['input1'], - ['output'], - to=TensorProto.INT8 - ), -] -graph_def = helper.make_graph( - nodes, - 'cast', - [INPUT_1], - [OUTPUT], -) -model_def = helper.make_model(graph_def, producer_name='cast_float_int8.py', opset_imports=[onnx.OperatorSetIdProto(version=12)]) -onnx.save(model_def, 'cast_float_int8.onnx') diff --git a/model-integration/src/test/models/onnx/cast_int8_float.onnx b/model-integration/src/test/models/onnx/cast_int8_float.onnx deleted file mode 100644 index 65aea4a36ae..00000000000 --- a/model-integration/src/test/models/onnx/cast_int8_float.onnx +++ /dev/null @@ -1,12 +0,0 @@ -cast_int8_float.py:U -! -input1output"Cast* -to castZ -input1 - - -b -output - - -B
\ No newline at end of file diff --git a/model-integration/src/test/models/onnx/cast_int8_float.py b/model-integration/src/test/models/onnx/cast_int8_float.py deleted file mode 100755 index 70bf2cf70ca..00000000000 --- a/model-integration/src/test/models/onnx/cast_int8_float.py +++ /dev/null @@ -1,24 +0,0 @@ -# Copyright Verizon Media. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. - -import onnx -from onnx import helper, TensorProto - -INPUT_1 = helper.make_tensor_value_info('input1', TensorProto.INT8, [1]) -OUTPUT = helper.make_tensor_value_info('output', TensorProto.FLOAT, [1]) - -nodes = [ - helper.make_node( - 'Cast', - ['input1'], - ['output'], - to=TensorProto.FLOAT - ), -] -graph_def = helper.make_graph( - nodes, - 'cast', - [INPUT_1], - [OUTPUT], -) -model_def = helper.make_model(graph_def, producer_name='cast_int8_float.py', opset_imports=[onnx.OperatorSetIdProto(version=12)]) -onnx.save(model_def, 'cast_int8_float.onnx') diff --git a/model-integration/src/test/models/onnx/pytorch/one_layer.onnx b/model-integration/src/test/models/onnx/pytorch/one_layer.onnx Binary files differdeleted file mode 100644 index dc9f664b943..00000000000 --- a/model-integration/src/test/models/onnx/pytorch/one_layer.onnx +++ /dev/null diff --git a/model-integration/src/test/models/onnx/pytorch/pytorch_one_layer.py b/model-integration/src/test/models/onnx/pytorch/pytorch_one_layer.py deleted file mode 100755 index 1296d84e180..00000000000 --- a/model-integration/src/test/models/onnx/pytorch/pytorch_one_layer.py +++ /dev/null @@ -1,38 +0,0 @@ -# Copyright Verizon Media. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. - -import torch -import torch.onnx - - -class MyModel(torch.nn.Module): - def __init__(self): - super(MyModel, self).__init__() - self.linear = torch.nn.Linear(in_features=3, out_features=1) - self.logistic = torch.nn.Sigmoid() - - def forward(self, vec): - return self.logistic(self.linear(vec)) - - -def main(): - model = MyModel() - - # Omit training - just export randomly initialized network - - data = torch.FloatTensor([[0.1, 0.2, 0.3],[0.4, 0.5, 0.6]]) - torch.onnx.export(model, - data, - "one_layer.onnx", - input_names = ["input"], - output_names = ["output"], - dynamic_axes = { - "input": {0: "batch"}, - "output": {0: "batch"}, - }, - opset_version=12) - - -if __name__ == "__main__": - main() - - diff --git a/model-integration/src/test/models/onnx/simple/matmul.onnx b/model-integration/src/test/models/onnx/simple/matmul.onnx deleted file mode 100644 index 9bb88406116..00000000000 --- a/model-integration/src/test/models/onnx/simple/matmul.onnx +++ /dev/null @@ -1,16 +0,0 @@ - matmul.py:x - -input1 -input2output"MatMulmatmulZ -input1 - - -Z -input2 - - -b -output - - -B
\ No newline at end of file diff --git a/model-integration/src/test/models/onnx/simple/matmul.py b/model-integration/src/test/models/onnx/simple/matmul.py deleted file mode 100755 index beec55e9f5a..00000000000 --- a/model-integration/src/test/models/onnx/simple/matmul.py +++ /dev/null @@ -1,27 +0,0 @@ -# Copyright 2020 Oath Inc. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root. - -import onnx -from onnx import helper, TensorProto - -INPUT1 = helper.make_tensor_value_info('input1', TensorProto.FLOAT, [2, 3]) -INPUT2 = helper.make_tensor_value_info('input2', TensorProto.FLOAT, [3, 4]) -OUTPUT = helper.make_tensor_value_info('output', TensorProto.FLOAT, [2, 4]) - -nodes = [ - helper.make_node( - 'MatMul', - ['input1', 'input2'], - ['output'], - ), -] -graph_def = helper.make_graph( - nodes, - 'matmul', - [ - INPUT1, - INPUT2, - ], - [OUTPUT], -) -model_def = helper.make_model(graph_def, producer_name='matmul.py', opset_imports=[onnx.OperatorSetIdProto(version=12)]) -onnx.save(model_def, 'matmul.onnx') diff --git a/parent/pom.xml b/parent/pom.xml index 25851a9553e..37350d77587 100644 --- a/parent/pom.xml +++ b/parent/pom.xml @@ -467,11 +467,6 @@ <version>1.4</version> </dependency> <dependency> - <groupId>com.microsoft.onnxruntime</groupId> - <artifactId>onnxruntime</artifactId> - <version>${onnxruntime.version}</version> - </dependency> - <dependency> <groupId>com.optimaize.languagedetector</groupId> <artifactId>language-detector</artifactId> <version>0.6</version> @@ -885,7 +880,6 @@ <maven-site-plugin.version>3.3</maven-site-plugin.version> <maven-source-plugin.version>3.0.1</maven-source-plugin.version> <prometheus.client.version>0.6.0</prometheus.client.version> - <onnxruntime.version>1.7.0</onnxruntime.version> <protobuf.version>3.11.4</protobuf.version> <spifly.version>1.3.3</spifly.version> <surefire.version>2.22.0</surefire.version> diff --git a/vespajlib/abi-spec.json b/vespajlib/abi-spec.json index 4ddf8b83cdc..ccdd09e4cab 100644 --- a/vespajlib/abi-spec.json +++ b/vespajlib/abi-spec.json @@ -897,7 +897,6 @@ "public com.yahoo.tensor.TensorType type()", "public abstract com.yahoo.tensor.IndexedTensor withType(com.yahoo.tensor.TensorType)", "public com.yahoo.tensor.DimensionSizes dimensionSizes()", - "public long[] shape()", "public java.util.Map cells()", "public com.yahoo.tensor.Tensor remove(java.util.Set)", "public java.lang.String toString()", diff --git a/vespajlib/src/main/java/com/yahoo/tensor/IndexedTensor.java b/vespajlib/src/main/java/com/yahoo/tensor/IndexedTensor.java index d822a5c6b8b..24578f035a3 100644 --- a/vespajlib/src/main/java/com/yahoo/tensor/IndexedTensor.java +++ b/vespajlib/src/main/java/com/yahoo/tensor/IndexedTensor.java @@ -191,14 +191,6 @@ public abstract class IndexedTensor implements Tensor { public DimensionSizes dimensionSizes() { return dimensionSizes; } - public long[] shape() { - long[] result = new long[dimensionSizes.dimensions()]; - for (int i = 0; i < result.length; ++i) { - result[i] = dimensionSizes.size(i); - } - return result; - } - @Override public Map<TensorAddress, Double> cells() { if (dimensionSizes.dimensions() == 0) |