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// _ _
// __ _____ __ ___ ___ __ _| |_ ___
// \ \ /\ / / _ \/ _` \ \ / / |/ _` | __/ _ \
// \ V V / __/ (_| |\ V /| | (_| | || __/
// \_/\_/ \___|\__,_| \_/ |_|\__,_|\__\___|
//
// Copyright © 2016 - 2024 Weaviate B.V. All rights reserved.
//
// CONTACT: [email protected]
//
package client
import (
"net/http"
"net/http/httptest"
"testing"
"time"
"github.com/stretchr/testify/assert"
)
func TestGetMeta(t *testing.T) {
t.Run("when the server is providing meta", func(t *testing.T) {
server := httptest.NewServer(&testMetaHandler{t: t})
defer server.Close()
c := New(server.URL, 0, nullLogger())
meta, err := c.MetaInfo()
assert.Nil(t, err)
assert.NotNil(t, meta)
metaModel := meta["model"]
assert.True(t, metaModel != nil)
model, modelOK := metaModel.(map[string]interface{})
assert.True(t, modelOK)
assert.True(t, model["_name_or_path"] != nil)
assert.True(t, model["architectures"] != nil)
})
}
type testMetaHandler struct {
t *testing.T
// the test handler will report as not ready before the time has passed
readyTime time.Time
}
func (f *testMetaHandler) ServeHTTP(w http.ResponseWriter, r *http.Request) {
assert.Equal(f.t, "/meta", r.URL.String())
assert.Equal(f.t, http.MethodGet, r.Method)
if time.Since(f.readyTime) < 0 {
w.WriteHeader(http.StatusServiceUnavailable)
}
w.Write([]byte(f.metaInfo()))
}
func (f *testMetaHandler) metaInfo() string {
return `{
"model": {
"_name_or_path": "dbmdz/bert-large-cased-finetuned-conll03-english",
"_num_labels": 9,
"add_cross_attention": false,
"architectures": [
"BertForTokenClassification"
],
"attention_probs_dropout_prob": 0.1,
"bad_words_ids": null,
"bos_token_id": null,
"chunk_size_feed_forward": 0,
"decoder_start_token_id": null,
"directionality": "bidi",
"diversity_penalty": 0,
"do_sample": false,
"early_stopping": false,
"encoder_no_repeat_ngram_size": 0,
"eos_token_id": null,
"finetuning_task": null,
"forced_bos_token_id": null,
"forced_eos_token_id": null,
"gradient_checkpointing": false,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 1024,
"id2label": {
"0": "O",
"1": "B-MISC",
"2": "I-MISC",
"3": "B-PER",
"4": "I-PER",
"5": "B-ORG",
"6": "I-ORG",
"7": "B-LOC",
"8": "I-LOC"
},
"initializer_range": 0.02,
"intermediate_size": 4096,
"is_decoder": false,
"is_encoder_decoder": false,
"label2id": {
"B-LOC": 7,
"B-MISC": 1,
"B-ORG": 5,
"B-PER": 3,
"I-LOC": 8,
"I-MISC": 2,
"I-ORG": 6,
"I-PER": 4,
"O": 0
},
"layer_norm_eps": 1e-12,
"length_penalty": 1,
"max_length": 20,
"max_position_embeddings": 512,
"min_length": 0,
"model_type": "bert",
"no_repeat_ngram_size": 0,
"num_attention_heads": 16,
"num_beam_groups": 1,
"num_beams": 1,
"num_hidden_layers": 24,
"num_return_sequences": 1,
"output_attentions": false,
"output_hidden_states": false,
"output_scores": false,
"pad_token_id": 0,
"pooler_fc_size": 768,
"pooler_num_attention_heads": 12,
"pooler_num_fc_layers": 3,
"pooler_size_per_head": 128,
"pooler_type": "first_token_transform",
"position_embedding_type": "absolute",
"prefix": null,
"problem_type": null,
"pruned_heads": {},
"remove_invalid_values": false,
"repetition_penalty": 1,
"return_dict": true,
"return_dict_in_generate": false,
"sep_token_id": null,
"task_specific_params": null,
"temperature": 1,
"tie_encoder_decoder": false,
"tie_word_embeddings": true,
"tokenizer_class": null,
"top_k": 50,
"top_p": 1,
"torchscript": false,
"transformers_version": "4.6.1",
"type_vocab_size": 2,
"use_bfloat16": false,
"use_cache": true,
"vocab_size": 28996
}
}`
}
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