Model: Add basic tests

We now do some basic tests for:
- hf torch loading (normal, lazy, lowmem)
- hf torch generation (shape batches, shape tokencount, faulty
  determinism)

Currently full determinism is failing; yahoo, the tests work!

All of the tests initally failed (note the test environment functions
different from the aiserver environment due to aiserver doing a lot of
initalizing stuff, working on phasing that out) but now only one fails.
Very useful for finding bugs!

modeling/test_generation.py

@@ -0,0 +1,47 @@
+# We have to go through aiserver to initalize koboldai_vars :(
+import torch
+from aiserver import GenericHFTorchInferenceModel
+from aiserver import koboldai_vars
+from modeling.inference_model import InferenceModel
+
+model: InferenceModel
+
+# Preferably teeny tiny
+TEST_MODEL_HF_ID = "EleutherAI/pythia-70m"
+TEST_PROMPT = "Once upon a time I found myself"
+TEST_GEN_TOKEN_COUNT = 20
+
+
+def test_generic_hf_torch_load() -> None:
+    global model
+    model = GenericHFTorchInferenceModel(
+        TEST_MODEL_HF_ID, lazy_load=False, low_mem=False
+    )
+    model.load()
+
+
+def test_generic_hf_torch_lazy_load() -> None:
+    GenericHFTorchInferenceModel(TEST_MODEL_HF_ID, lazy_load=True, low_mem=False).load()
+
+
+def test_generic_hf_torch_low_mem_load() -> None:
+    GenericHFTorchInferenceModel(TEST_MODEL_HF_ID, lazy_load=False, low_mem=True).load()
+
+
+def test_model_gen() -> None:
+    # This should probably be supported in the model interface!
+    koboldai_vars.full_determinism = True
+    koboldai_vars.seed = 1337
+
+    x = model.raw_generate(TEST_PROMPT, max_new=TEST_GEN_TOKEN_COUNT)
+    print(x.decoded)
+    assert len(x.encoded) == 1, "Bad output shape (too many batches!)"
+    assert len(x.encoded[0]) == 20, "Wrong token amount (requested 20)"
+
+    y = model.raw_generate(TEST_PROMPT, max_new=TEST_GEN_TOKEN_COUNT)
+
+    assert torch.equal(
+        x.encoded[0], y.encoded[0]
+    ), f"Faulty full determinism! {x.decoded} vs {y.decoded}"
+
+    print(x)