Merge https://github.com/pytorch/pytorch into flatten

.github/workflows/quantization_triage.yml

@@ -0,0 +1,78 @@
+name: quantization-triage
+
+on:
+  issues:
+    types: [labeled]
+
+jobs:
+  welcome:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/github-script@v2
+        with:
+          github-token: ${{secrets.GITHUB_TOKEN}}
+          script: |
+            // Arguments available:
+            // - github: A pre-authenticated octokit/rest.js client
+            // - context: An object containing the context of the workflow run
+            // - core: A reference to the @actions/core package
+            // - io: A reference to the @actions/io package
+
+            // Check if issue has a Quantization label.
+            const kQuantizationLabel = "oncall: quantization";
+
+            issue = await github.issues.get({
+              owner: context.issue.owner,
+              repo: context.issue.repo,
+              issue_number: context.issue.number,
+            })
+
+            const hasQuantizationLabel = issue.data.labels.filter(label => label.name == kQuantizationLabel).length > 0;
+
+            if (!hasQuantizationLabel) {
+              core.debug("Issue " + issue.data.title + " does not have Quantization label");
+              return;
+            }
+
+            // Get project column ID.
+            const kProjectName = "Quantization Triage";
+            const kColumnName = "Need Triage";
+
+            // Query all projects in the repository.
+            // TODO: Support pagination once there are > 30 projects.
+            const projects = await github.projects.listForRepo({
+              owner: context.issue.owner,
+              repo: context.issue.repo,
+            });
+
+            // Filter out unwanted projects and get the ID for the Quantization Triage project.
+            const filteredProjects = projects.data.filter(project => project.name == kProjectName);
+
+            if (filteredProjects.length != 1) {
+              core.setFailed("Unable to find a project named " + kProjectName);
+              return;
+            }
+
+            const projectId = filteredProjects[0].id;
+            // First, query all columns in the project.
+            // TODO: Support pagination once there are > 30 columns.
+            const columns = await github.projects.listColumns({
+              project_id: projectId,
+            });
+
+            // Filter out unwanted projects and get the ID for the Need triage column.
+            const filteredColumns = columns.data.filter(column => column.name == kColumnName);
+
+            if (filteredColumns.length != 1) {
+              core.setFailed("Unable to find a column named " + kColumnName);
+              return;
+            }
+
+            const columnId = filteredColumns[0].id;
+
+            // Create a project card for this new issue.
+            await github.projects.createCard({
+              column_id: columnId,
+              content_id: issue.data.id,
+              content_type: "Issue",
+            })

test/test_fx.py

@@ -7,7 +7,6 @@
 from pathlib import Path
 from torch.fx import symbolic_trace, Proxy, Node, GraphModule, Tracer, Graph
 from torch.fx.experimental import GraphManipulation
-from torch.fx.experimental import shape_prop
 
 from torch.fx.proxy import TraceError
 
@@ -734,31 +733,5 @@ def test_wrong_topo(self):
         with self.assertRaisesRegex(RuntimeError, 'was used before it has been defined'):
             graph.lint()
 
-    def test_example_shape_prop(self):
-        class TestCase(torch.nn.Module):
-            def __init__(self):
-                super().__init__()
-                self.attr = torch.randn(3, 4)
-                self.submod = torch.nn.Linear(4, 4)
-
-            def forward(self, x):
-                return torch.neg(self.submod(x.relu() + self.attr))
-        tc = TestCase()
-        tc_traced = symbolic_trace(tc)
-        ref_out = tc_traced(torch.rand(3, 4))
-
-        # Make sure we're testing all opcodes
-        opcodes = set()
-        for node in tc_traced.graph.nodes:
-            opcodes.add(node.op)
-        self.assertEqual(opcodes, set(['placeholder', 'get_attr', 'call_function', 'call_method', 'call_module']))
-
-        # Test shape propogation and make sure results match actual
-        shape_prop.ShapeProp(tc_traced).propagate(torch.rand(3, 4))
-        self.assertEqual(tc_traced.graph.result.shape, ref_out.shape)
-
-
-
-
 if __name__ == '__main__':
     run_tests()

torch/csrc/jit/ir/ir.cpp

@@ -326,6 +326,8 @@ std::ostream& Graph::print(std::ostream& out, bool print_source_locations)
     out << "with " << fg->kind().toQualString() << "_" << i++ << " = "
         << *fg->g(attr::Subgraph);
   }
+  out.flush();
+
   /*
   // Uncomment this to debug all_nodes issues
   {