make --device fast the default (pytorch#515)

* make --device fast the default

* Update iOS.md (pytorch#517)

* Update iOS.md

* Update iOS.md

* Pip to pip3 (pytorch#504)

* remove macos-12 test

* pip to pip3

* break aoti CI jobs separately (pytorch#500)

* init

* fixes

* more fixes

* fixes

* fix

* fix

* bug fix

* add objcopy update

* suppress int8

* undefined variable

---------

Co-authored-by: Michael Gschwind <[email protected]>

* Support llama3 in chat in run.cpp  (pytorch#486)

* refactor chat runner in preparation for llama3

* add sketch for llama3 prompt template and move to returning tokens

* fix tiktoken

* fixes to chat

* add default llama_ver

* Add tests for quantize json, add cuda device specification and precision to cuda.json (pytorch#519)

* remove code for no KV Cache path (pytorch#527)

* Update ADVANCED-USERS.md (pytorch#529)

Update Advanced Users description to reflect changes in the repo since the description was initially created.

* runner-aoti on cuda (pytorch#531)

* runner-aoti on cuda

* transfer results back to CPU

* transfer results back to CPU

* runner-aoti on cuda

* Update runner_build.md (pytorch#530)

Update description of runner and build process in runner_build.md

* clean up runner code a little (pytorch#532)

* clean up runner code a little

* update

* update

* pull out generate loop in chat

* updates

* edit docs

* typo

* move int8 linear class and function into qops.py (pytorch#534)

* add dtype tests for runner-aoti + runner-et (pytorch#539)

* add dtype tests for runner-aoti + runner-et

* typo

* Quantized embedding (pytorch#536)

* move int8 linear class and function into qops.py

* move Quantized Embedding to qops.py

* Move Linear int4 to qops (pytorch#537)

* move int8 linear class and function into qops.py

* move Quantized Embedding to qops.py

* move int4 linear to qops

* Revert "add dtype tests for runner-aoti + runner-et (pytorch#539)" (pytorch#548)

This reverts commit a7a24577a65be67ac9ae4dc05452f35d9c49e5d1.

* fix generate for llama3 (pytorch#538)

* fix generate for llama3

* switch more things to C

* remove C++ header

* add delegation visualization instructions (pytorch#551)

* Add dtype runner aoti (pytorch#552)

* add dtype tests for runner-aoti + runner-et

* typo

* add dtype test runner-aoti

* test sdpa with fp16 (pytorch#553)

* test sdpa with fp16

* kv cache fp32

* typo

* update (pytorch#560)

* Only support newest versions of lm-eval (pytorch#556)

Summary:
remove support for lm-eval 0.3 to reduce the options we have

Test Plan:
CI

Reviewers:

Subscribers:

Tasks:

Tags:

* split cpu eval CI by dtype (pytorch#554)

* split cpu eval CI by dtype

* fix

* differentiate names with checks

* keep one name the same as old

* fix

* Removing duplicate HF issue message from README (pytorch#559)

Co-authored-by: Michael Gschwind <[email protected]>

* doc updates (pytorch#567)

* Add VM-safe MPS check

---------

Co-authored-by: Anthony Shoumikhin <[email protected]>
Co-authored-by: metascroy <[email protected]>
Co-authored-by: Nikita Shulga <[email protected]>
Co-authored-by: lucylq <[email protected]>
Co-authored-by: Jerry Zhang <[email protected]>
Co-authored-by: Jack-Khuu <[email protected]>

Author: 7 people

build/utils.py

@@ -156,13 +156,27 @@ def state_dict_device(d, device="cpu") -> Dict:
 #########################################################################
 ###                move state dict to specified device                ###
 
+def is_mps_available() -> bool:
+    if not torch.backends.mps.is_available():
+        return False
+
+    # out system says mps is available, but it's not on VMs
+    # so let's set up some memry, and see if that work:
+    try:
+        mps_tensor = torch.zero(1024, dtype=torch.float16, device="mps")
+    except:
+        return False
+
+    # MPS, is that you? 
+    return True
+
 
 def get_device_str(device) -> str:
     if isinstance(device, str) and device == "fast":
         return (
             "cuda"
             if torch.cuda.is_available()
-            else "mps" if torch.backends.mps.is_available() else "cpu"
+            else "mps" if is_mps_available() else "cpu"
         )
     else:
         return str(device)
@@ -173,6 +187,6 @@ def get_device(device) -> str:
         device = (
             "cuda"
             if torch.cuda.is_available()
-            else "mps" if torch.backends.mps.is_available() else "cpu"
+            else "mps" if is_mps_available() else "cpu"
         )
     return torch.device(device)

cli.py

@@ -12,7 +12,7 @@
 from build.utils import allowable_dtype_names, allowable_params_table, get_device_str
 from download import download_and_convert, is_model_downloaded
 
-default_device = "cpu"
+default_device = "fast"
 
 
 # Handle CLI arguments that are common to a majority of subcommands.

generate.py

@@ -210,7 +210,7 @@ def decode_n_tokens(
 ):
     new_tokens, new_probs = [], []
     encountered_eos = False
-    for i in range(
+    for _i in range(
         num_new_tokens - 1
     ):  # -1 to save space to run an EoS if dont generate it naturally
         # Actually better for Inductor to codegen attention here