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 /model-integration/src/test | |
parent | 390a26e1a42486fefedef5468c86a781d1d833d1 (diff) |
Revert "Add ONNX-RT evaluator to model-integration module"
Diffstat (limited to 'model-integration/src/test')
17 files changed, 0 insertions, 411 deletions
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') |