Add torch.set_num_threads for ptq tests (#1995)

### Changes

Set number of thread for torch backends for
`torch.set_num_threads(int(cpu_threads_num))` by set `CPU_THREADS_NUM`
env variable.

Example of reducing quantization time for TORCH backend:

Model | Before | After  
--- | --- | --- 
deit3_small_patch16_224 | 2:34:09  | 0:00:46
dla34 | 0:16:38  | 0:00:38

Build: manual/post_training_quantization/122

Renamed tests to `test_ptq_quantization`

### Reason for changes

Quantization time is dramatically slow for TORCH backends on CI.

tests/post_training/pipelines/base.py

@@ -8,6 +8,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+import os
 import time
 from abc import ABC
 from abc import abstractmethod
@@ -212,6 +213,12 @@ def quantize(self) -> None:
         Run quantization of the model and collect time and memory usage information.
         """
         print("Quantization...")
+
+        if self.backend in [BackendType.TORCH, BackendType.OLD_TORCH]:
+            cpu_threads_num = os.environ.get("CPU_THREADS_NUM")
+            if cpu_threads_num is not None:
+                torch.set_num_threads(int(cpu_threads_num))
+
         start_time = time.perf_counter()
         self.run_info.quant_memory_usage = memory_usage(self._quantize, max_usage=True)
         self.run_info.time_quantization = time.perf_counter() - start_time

tests/post_training/test_quantize_conformance.py

@@ -48,7 +48,7 @@ def read_reference_data():
 
 
 @pytest.mark.parametrize("test_case_name", TEST_CASES.keys())
-def test_ptq_hf(test_case_name, data, output, result):
+def test_ptq_quantization(test_case_name, data, output, result):
     pipeline = None
     err_msg = None
     test_model_param = None