Add type error suppressions for upcoming upgrade (#3504)

Summary:
X-link: facebookresearch/FBGEMM#584

Pull Request resolved: #3504

Reviewed By: Solumin

Differential Revision: D67162164

fbshipit-source-id: 6a781090bbec3ef502a574d456cc6eddc3a260be

fbgemm_gpu/test/quantize/common.py

@@ -16,6 +16,7 @@
 import torch
 
 # pyre-fixme[16]: Module `fbgemm_gpu` has no attribute `open_source`.
+# pyre-fixme[35]: Target cannot be annotated.
 open_source: bool = getattr(fbgemm_gpu, "open_source", False)
 
 try:

fbgemm_gpu/test/quantize/fp8_rowwise_test.py

@@ -22,6 +22,7 @@
 #  `deeplearning.fbgemm.fbgemm_gpu.test.quantize.common`.
 from .common import open_source
 
+# pyre-fixme[16]: Module `common` has no attribute `open_source`.
 if open_source:
     # pyre-ignore[21]
     from test_utils import gpu_unavailable, optests, symint_vector_unsupported

fbgemm_gpu/test/quantize/fused_8bit_rowwise_test.py

@@ -25,6 +25,7 @@
     open_source,
 )
 
+# pyre-fixme[16]: Module `common` has no attribute `open_source`.
 if open_source:
     # pyre-ignore[21]
     from test_utils import gpu_available

fbgemm_gpu/test/quantize/fused_nbit_rowwise_test.py

@@ -25,6 +25,7 @@
     open_source,
 )
 
+# pyre-fixme[16]: Module `common` has no attribute `open_source`.
 if open_source:
     # pyre-ignore[21]
     from test_utils import gpu_available, optests

fbgemm_gpu/test/quantize/mixed_dim_int8_test.py

@@ -20,6 +20,7 @@
 #  `deeplearning.fbgemm.fbgemm_gpu.test.quantize.common`.
 from .common import open_source
 
+# pyre-fixme[16]: Module `common` has no attribute `open_source`.
 if open_source:
     # pyre-ignore[21]
     from test_utils import gpu_unavailable

fbgemm_gpu/test/quantize/msfp_test.py

@@ -18,6 +18,7 @@
 #  `deeplearning.fbgemm.fbgemm_gpu.test.quantize.common`.
 from .common import open_source
 
+# pyre-fixme[16]: Module `common` has no attribute `open_source`.
 if open_source:
     # pyre-ignore[21]
     from test_utils import gpu_unavailable

fbgemm_gpu/test/quantize/mx/common.py

@@ -312,6 +312,7 @@ def check_diff_quantize(
     # Convert to numpy
     # pyre-fixme[9]: x has type `Tensor`; used as `Union[ndarray, Tensor]`.
     x = np.array(x) if type(x) is list else x
+    # pyre-fixme[9]: x has type `Tensor`; used as `Union[ndarray[Any, Any], Tensor]`.
     x = x.cpu().numpy() if type(x) is torch.Tensor else x
     y1 = y1.detach().cpu().numpy()
     y2 = y2.detach().cpu().numpy()
@@ -334,11 +335,13 @@ def check_diff_quantize(
         where_diff = (diff != 0) | (torch_infs != cuda_infs)
         print("%d/%d mismatches" % (np.count_nonzero(where_diff), where_diff.size))
         print("First and last mismatch:")
+        # pyre-fixme[6]: For 1st argument expected `float` but got `Tensor`.
         print("Orig:", x[where_diff][0], get_s_e_m(x[where_diff][0]))
         print("y1:  ", y1[where_diff][0], get_s_e_m(y1[where_diff][0]))
         print("y2:  ", y2[where_diff][0], get_s_e_m(y2[where_diff][0]))
         if np.count_nonzero(where_diff) > 1:
             print("--------------------")
+            # pyre-fixme[6]: For 1st argument expected `float` but got `Tensor`.
             print("Orig:", x[where_diff][-1], get_s_e_m(x[where_diff][-1]))
             print("y1:  ", y1[where_diff][-1], get_s_e_m(y1[where_diff][-1]))
             print("y2:  ", y2[where_diff][-1], get_s_e_m(y2[where_diff][-1]))

fbgemm_gpu/test/quantize/mx4_test.py

@@ -34,6 +34,7 @@
     check_diff_quantize,
 )
 
+# pyre-fixme[16]: Module `common` has no attribute `open_source`.
 if open_source:
     # pyre-ignore[21]
     from test_utils import gpu_unavailable

fbgemm_gpu/test/tbe/cache/lxu_cache_test.py

@@ -171,6 +171,7 @@ def test_unique_lxu_cache_lookup(
             use_cpu=False,
         ).long()
 
+        # pyre-fixme[53]: Captured variable `lxu_cache_state` is not annotated.
         def unique_lookup(
             indices: Tensor,
             offsets: Tensor,
@@ -197,6 +198,7 @@ def unique_lookup(
 
             return uniq_lxu_cache_locations, uniq_indices_length
 
+        # pyre-fixme[53]: Captured variable `lxu_cache_state` is not annotated.
         def duplicate_lookup(
             indices: Tensor,
             offsets: Tensor,