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Improve resource management in TransformersEmbeddingModel #1504

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51 changes: 28 additions & 23 deletions ...formers/src/main/java/org/springframework/ai/transformers/TransformersEmbeddingModel.java
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Original file line number Diff line number Diff line change
Expand Up @@ -291,39 +291,44 @@ public EmbeddingResponse call(EmbeddingRequest request) {
token_type_ids0[i] = encodings[i].getTypeIds();
}

OnnxTensor inputIds = OnnxTensor.createTensor(this.environment, input_ids0);
OnnxTensor attentionMask = OnnxTensor.createTensor(this.environment, attention_mask0);
OnnxTensor tokenTypeIds = OnnxTensor.createTensor(this.environment, token_type_ids0);
try (OnnxTensor inputIds = OnnxTensor.createTensor(this.environment, input_ids0);
OnnxTensor attentionMask = OnnxTensor.createTensor(this.environment, attention_mask0);
OnnxTensor tokenTypeIds = OnnxTensor.createTensor(this.environment, token_type_ids0);) {

Map<String, OnnxTensor> modelInputs = Map.of("input_ids", inputIds, "attention_mask", attentionMask,
"token_type_ids", tokenTypeIds);
Map<String, OnnxTensor> modelInputs = Map.of("input_ids", inputIds, "attention_mask",
attentionMask, "token_type_ids", tokenTypeIds);

modelInputs = removeUnknownModelInputs(modelInputs);
modelInputs = removeUnknownModelInputs(modelInputs);

// The Run result object is AutoCloseable to prevent references from
// leaking
// out. Once the Result object is
// closed, all it’s child OnnxValues are closed too.
try (OrtSession.Result results = this.session.run(modelInputs)) {
// The Run result object is AutoCloseable to prevent references
// from leaking out. Once the Result object is
// closed, all it’s child OnnxValues are closed too.
try (OrtSession.Result results = this.session.run(modelInputs)) {

// OnnxValue lastHiddenState = results.get(0);
OnnxValue lastHiddenState = results.get(this.modelOutputName).get();
// OnnxValue lastHiddenState = results.get(0);
OnnxValue lastHiddenState = results.get(this.modelOutputName).get();

// 0 - batch_size (1..x)
// 1 - sequence_length (128)
// 2 - embedding dimensions (384)
float[][][] tokenEmbeddings = (float[][][]) lastHiddenState.getValue();
// 0 - batch_size (1..x)
// 1 - sequence_length (128)
// 2 - embedding dimensions (384)
float[][][] tokenEmbeddings = (float[][][]) lastHiddenState.getValue();

try (NDManager manager = NDManager.newBaseManager()) {
NDArray ndTokenEmbeddings = create(tokenEmbeddings, manager);
NDArray ndAttentionMask = manager.create(attention_mask0);
try (NDManager manager = NDManager.newBaseManager()) {
NDArray ndTokenEmbeddings = create(tokenEmbeddings, manager);
NDArray ndAttentionMask = manager.create(attention_mask0);

NDArray embedding = meanPooling(ndTokenEmbeddings, ndAttentionMask);
NDArray embedding = meanPooling(ndTokenEmbeddings, ndAttentionMask);

for (int i = 0; i < embedding.size(0); i++) {
resultEmbeddings.add(embedding.get(i).toFloatArray());
for (int i = 0; i < embedding.size(0); i++) {
resultEmbeddings.add(embedding.get(i).toFloatArray());
}
}
}
finally {
inputIds.close();
attentionMask.close();
tokenTypeIds.close();
}
}
}
catch (OrtException ex) {
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