adding tests for embedding and similarity

src/backend/api/matching_algorithm.py

@@ -1,4 +1,5 @@
 from typing import List
+import torch
 from sklearn.metrics.pairwise import cosine_similarity
 
 
@@ -27,3 +28,9 @@ def get_free_text_match(
         return 0
 
     return cosine_similarity(candidate_embeddings, job_embeddings)[0][0]
+
+if __name__=="__main__":
+    print(int(get_free_text_match(
+    torch.tensor([[1,0,0]]),
+    torch.tensor([[-1,0,0]]),
+))==-1)

src/backend/api/tokenization_n_embedding.py

@@ -1,7 +1,6 @@
 import torch
 from typing import List
 from transformers import AutoTokenizer, AutoModel
-from sklearn.metrics.pairwise import cosine_similarity
 
 
 MODEL_NAME = "bert-base-uncased"
@@ -46,3 +45,6 @@ def generate_embeddings(text: str, model_name: str=MODEL_NAME) -> List[List]:
     text_embeddings = text_outputs.last_hidden_state.mean(dim=1)
     return text_embeddings
 
+if __name__=="__main__":
+    s = ""
+    print(generate_embeddings(s)[0][0].item()==-0.00922924280166626)

tests/test_embedding_similarity.py

@@ -0,0 +1,35 @@
+import torch
+import sys
+import os
+current = os.path.dirname(os.path.realpath('tokenization_n_embedding.py'))
+parent = os.path.dirname(current)
+sys.path.append(parent)
+from src.backend.api.tokenization_n_embedding import tokenize_text, generate_embeddings
+from src.backend.api.matching_algorithm import get_free_text_match
+
+def test_tokenize_text():
+    text_tokens_keys = set(['input_ids','token_type_ids','attention_mask'])
+    assert set(tokenize_text("test").keys()) == \
+        text_tokens_keys
+    assert set(tokenize_text("").keys()) == \
+        text_tokens_keys
+
+def generate_embeddings():
+    assert len(generate_embeddings("any text")) == 1
+    assert len(generate_embeddings("any text")[0]) == 768
+    assert generate_embeddings("").dtype == torch.float32
+    assert generate_embeddings("")[0][0].item()==-0.00922924280166626
+
+def get_free_text_match_text():
+    assert get_free_text_match(int(
+            torch.tensor([[1,2,3]]),
+            torch.tensor([[-1,-2,-3]])
+    )) == -1
+    assert get_free_text_match(int(
+            torch.tensor([[1,2,3]]),
+            torch.tensor([[1,2,3]])
+    )) == 1
+    assert get_free_text_match(int(
+    torch.tensor([[1,0,0]]),
+    torch.tensor([[0,1,0]]),
+    )) == 0