[GitHub] [tvm] AndrewZhaoLuo commented on a diff in pull request #11000: [Graph Debugger] Expose way to benchmark individual nodes.
AndrewZhaoLuo commented on code in PR #11000:
URL: https://github.com/apache/tvm/pull/11000#discussion_r858230661
##
tests/python/unittest/test_runtime_graph_debug.py:
##
@@ -185,5 +191,47 @@ def check_remote(server):
check_remote(rpc.Server("127.0.0.1"))
+@tvm.testing.requires_llvm
+def test_run_single_node(graph):
+mlib_proxy = tvm.support.FrontendTestModule()
+mlib_proxy["myadd"] = myadd
+try:
+mod: debug_executor.GraphModuleDebug = debug_executor.create(graph,
mlib_proxy, tvm.cpu(0))
+except ValueError:
+return
Review Comment:
Cool, done
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[GitHub] [tvm] AndrewZhaoLuo commented on a diff in pull request #11000: [Graph Debugger] Expose way to benchmark individual nodes.
AndrewZhaoLuo commented on code in PR #11000:
URL: https://github.com/apache/tvm/pull/11000#discussion_r858100679
##
tests/python/unittest/test_runtime_graph_debug.py:
##
@@ -19,26 +19,34 @@
import re
import sys
import time
+from distutils.log import debug
+import numpy as np
import pytest
-
import tvm
import tvm.testing
-from tvm import te
-import numpy as np
-from tvm import rpc
+from tvm import rpc, te
+from tvm._ffi.base import TVMError
from tvm.contrib import utils
from tvm.contrib.debugger import debug_executor
+# Constants for creating simple graphs
+n = 4
+A = te.placeholder((n,), name="A")
+B = te.compute(A.shape, lambda *i: A(*i) + 1.0, name="B")
+s = te.create_schedule(B.op)
Review Comment:
Done
##
tests/python/unittest/test_runtime_graph_debug.py:
##
@@ -185,5 +191,47 @@ def check_remote(server):
check_remote(rpc.Server("127.0.0.1"))
+@tvm.testing.requires_llvm
+def test_run_single_node(graph):
+mlib_proxy = tvm.support.FrontendTestModule()
+mlib_proxy["myadd"] = myadd
+try:
+mod: debug_executor.GraphModuleDebug = debug_executor.create(graph,
mlib_proxy, tvm.cpu(0))
+except ValueError:
+return
+
+a = np.random.uniform(size=(n,)).astype(A.dtype)
+mod.set_input(x=a)
+
+assert len(mod.debug_datum.get_graph_nodes()) == 2
+assert mod.debug_datum.get_graph_nodes()[0]["op"] == "param"
+assert mod.debug_datum.get_graph_nodes()[1]["op"] == "myadd"
+
+# Running a node with no associated function should return instantly and
have 0 runtime
+mod.run_individual_node(0, number=1).mean == 0
Review Comment:
Oopsy, done
##
tests/python/unittest/test_runtime_graph_debug.py:
##
@@ -185,5 +191,47 @@ def check_remote(server):
check_remote(rpc.Server("127.0.0.1"))
+@tvm.testing.requires_llvm
+def test_run_single_node(graph):
+mlib_proxy = tvm.support.FrontendTestModule()
+mlib_proxy["myadd"] = myadd
+try:
+mod: debug_executor.GraphModuleDebug = debug_executor.create(graph,
mlib_proxy, tvm.cpu(0))
+except ValueError:
+return
+
+a = np.random.uniform(size=(n,)).astype(A.dtype)
+mod.set_input(x=a)
+
+assert len(mod.debug_datum.get_graph_nodes()) == 2
+assert mod.debug_datum.get_graph_nodes()[0]["op"] == "param"
+assert mod.debug_datum.get_graph_nodes()[1]["op"] == "myadd"
+
+# Running a node with no associated function should return instantly and
have 0 runtime
+mod.run_individual_node(0, number=1).mean == 0
+
+# Meanwhile the actual function should take some time, more time if you
run it more times
+repeat_1_result = mod.run_individual_node(1, repeat=1)
+repeat_1_result.mean > 0
Review Comment:
Oopsy, done
##
tests/python/unittest/test_runtime_graph_debug.py:
##
@@ -185,5 +191,47 @@ def check_remote(server):
check_remote(rpc.Server("127.0.0.1"))
+@tvm.testing.requires_llvm
+def test_run_single_node(graph):
+mlib_proxy = tvm.support.FrontendTestModule()
+mlib_proxy["myadd"] = myadd
+try:
+mod: debug_executor.GraphModuleDebug = debug_executor.create(graph,
mlib_proxy, tvm.cpu(0))
+except ValueError:
+return
Review Comment:
This will be hit if TVM is not built with the profiler on. Added a comment
clarifying
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[GitHub] [tvm] AndrewZhaoLuo commented on a diff in pull request #11000: [Graph Debugger] Expose way to benchmark individual nodes.
AndrewZhaoLuo commented on code in PR #11000:
URL: https://github.com/apache/tvm/pull/11000#discussion_r856618731
##
src/runtime/graph_executor/debug/graph_executor_debug.cc:
##
@@ -114,15 +94,69 @@ class GraphExecutorDebug : public GraphExecutor {
std::ostringstream os;
for (size_t index = 0; index < time_sec_per_op.size(); index++) {
- os << time_sec_per_op[index] << ",";
+ double time = time_sec_per_op[index];
+ // To have good behavior when calculating total time, etc.
+ if (isnan(time)) {
+time = 0;
+ }
+ os << time << ",";
}
return os.str();
}
+ std::vector> RunIndividualNode(int node_index, int
number, int repeat,
+ int min_repeat_ms) {
+// warmup run
+// GraphExecutor::Run();
+std::string tkey = module_->type_key();
+
+// results_in_seconds[a][b] is the bth index run of the ath index repeat
+std::vector> results_in_seconds;
+
+if (tkey == "rpc") {
+ LOG(FATAL) << "RPC measurements should not use RunIndividualNode!";
+}
+
+for (int i = 0; i < repeat; ++i) {
+ std::vector op_timers;
+ double duration_ms = 0.0;
+
+ // Keep timing operations, upping number of repeats until we reach
min_repeat_ms
+ do {
+op_timers.clear();
+if (duration_ms > 0.0) {
+ number = static_cast(std::max((min_repeat_ms / (duration_ms /
number) + 1),
+ number * 1.618)); // 1.618 is
chosen by random
+}
+
+std::chrono::time_point
+tbegin, tend;
+tbegin = std::chrono::high_resolution_clock::now();
Review Comment:
Done, it now uses the linked time evaluator. Lots of deduped code B)
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[GitHub] [tvm] AndrewZhaoLuo commented on a diff in pull request #11000: [Graph Debugger] Expose way to benchmark individual nodes.
AndrewZhaoLuo commented on code in PR #11000:
URL: https://github.com/apache/tvm/pull/11000#discussion_r856618606
##
python/tvm/contrib/debugger/debug_executor.py:
##
@@ -281,6 +282,42 @@ def run_individual(self, number, repeat=1,
min_repeat_ms=0):
ret = self._run_individual(number, repeat, min_repeat_ms)
return ret.strip(",").split(",") if ret else []
+def run_individual_node(self, index, number, repeat=1, min_repeat_ms=0):
+"""Benchmark a single node in the serialized graph.
+
+Parameters
+--
+index : int
+The index of the node, see `self.debug_datum.get_graph_nodes`
+
+number: int
+The number of times to run the node to get a benchmark result.
+
+repeat: int
+The number of times to benchmark the nodes.
Review Comment:
Done
##
python/tvm/contrib/debugger/debug_executor.py:
##
@@ -281,6 +282,42 @@ def run_individual(self, number, repeat=1,
min_repeat_ms=0):
ret = self._run_individual(number, repeat, min_repeat_ms)
return ret.strip(",").split(",") if ret else []
+def run_individual_node(self, index, number, repeat=1, min_repeat_ms=0):
+"""Benchmark a single node in the serialized graph.
+
+Parameters
+--
+index : int
+The index of the node, see `self.debug_datum.get_graph_nodes`
+
+number: int
+The number of times to run the node to get a benchmark result.
+
+repeat: int
+The number of times to benchmark the nodes.
+
+min_repeat_ms: int
+The minimum consecutive runtime of the node for a benchmark result.
+
+Returns
+---
+A list of dimensions `number` x `repeat` each one the runtime of the
node
Review Comment:
Done
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[GitHub] [tvm] AndrewZhaoLuo commented on a diff in pull request #11000: [Graph Debugger] Expose way to benchmark individual nodes.
AndrewZhaoLuo commented on code in PR #11000:
URL: https://github.com/apache/tvm/pull/11000#discussion_r852460978
##
python/tvm/contrib/debugger/debug_executor.py:
##
@@ -281,6 +282,42 @@ def run_individual(self, number, repeat=1,
min_repeat_ms=0):
ret = self._run_individual(number, repeat, min_repeat_ms)
return ret.strip(",").split(",") if ret else []
+def run_individual_node(self, index, number, repeat=1, min_repeat_ms=0):
+"""Benchmark a single node in the serialized graph.
Review Comment:
Done
##
python/tvm/contrib/debugger/debug_executor.py:
##
@@ -281,6 +282,42 @@ def run_individual(self, number, repeat=1,
min_repeat_ms=0):
ret = self._run_individual(number, repeat, min_repeat_ms)
return ret.strip(",").split(",") if ret else []
+def run_individual_node(self, index, number, repeat=1, min_repeat_ms=0):
+"""Benchmark a single node in the serialized graph.
+
+Parameters
+--
+index : int
+The index of the node, see `self.debug_datum.get_graph_nodes`
+
+number: int
+The number of times to run the node to get a benchmark result.
+
+repeat: int
+The number of times to benchmark the nodes.
+
+min_repeat_ms: int
+The minimum consecutive runtime of the node for a benchmark result.
+
+Returns
+---
+A list of dimensions `number` x `repeat` each one the runtime of the
node
Review Comment:
Basically if have like 3 repeats of 3 numbers it would return a 3x3
array/list.
arr[0][1] would be the first repeat in the second number, arr[1][2] would be
the repeat 2, number 3, etc.
I think BenchmarkResult is better though since it seems to store the
sequence of all float results anyway?
##
python/tvm/contrib/debugger/debug_executor.py:
##
@@ -281,6 +282,42 @@ def run_individual(self, number, repeat=1,
min_repeat_ms=0):
ret = self._run_individual(number, repeat, min_repeat_ms)
return ret.strip(",").split(",") if ret else []
+def run_individual_node(self, index, number, repeat=1, min_repeat_ms=0):
Review Comment:
done
##
python/tvm/contrib/debugger/debug_executor.py:
##
@@ -281,6 +282,42 @@ def run_individual(self, number, repeat=1,
min_repeat_ms=0):
ret = self._run_individual(number, repeat, min_repeat_ms)
return ret.strip(",").split(",") if ret else []
+def run_individual_node(self, index, number, repeat=1, min_repeat_ms=0):
+"""Benchmark a single node in the serialized graph.
+
+Parameters
+--
+index : int
+The index of the node, see `self.debug_datum.get_graph_nodes`
+
+number: int
+The number of times to run the node to get a benchmark result.
+
+repeat: int
+The number of times to benchmark the nodes.
Review Comment:
I'll probably just use time_evaluator, so will change later.
##
src/runtime/graph_executor/debug/graph_executor_debug.cc:
##
@@ -362,6 +396,33 @@ PackedFunc GraphExecutorDebug::GetFunction(const
std::string& name,
ICHECK_GE(min_repeat_ms, 0);
*rv = this->RunIndividual(number, repeat, min_repeat_ms);
});
+ } else if (name == "run_individual_node") {
+return PackedFunc([sptr_to_self, this](TVMArgs args, TVMRetValue* rv) {
+ int node_index = args[0];
+ int number = args[1];
+ int repeat = args[2];
+ int min_repeat_ms = args[3];
+ ICHECK_GE(node_index, 0);
+ ICHECK_LT(node_index, nodes_.size());
+ ICHECK_GT(number, 0);
+ ICHECK_GT(repeat, 0);
+ ICHECK_GE(min_repeat_ms, 0);
+ std::vector> results =
+ this->RunIndividualNode(node_index, number, repeat, min_repeat_ms);
+
+ std::stringstream s;
+ s.precision(6); // down to microseconds
Review Comment:
Done
##
src/runtime/graph_executor/debug/graph_executor_debug.cc:
##
@@ -114,15 +94,69 @@ class GraphExecutorDebug : public GraphExecutor {
std::ostringstream os;
for (size_t index = 0; index < time_sec_per_op.size(); index++) {
- os << time_sec_per_op[index] << ",";
+ double time = time_sec_per_op[index];
+ // To have good behavior when calculating total time, etc.
+ if (isnan(time)) {
+time = 0;
+ }
Review Comment:
0 / 0 is possible from the above for nodes which do not have any associated
execution function
##
src/runtime/graph_executor/debug/graph_executor_debug.cc:
##
@@ -114,15 +94,69 @@ class GraphExecutorDebug : public GraphExecutor {
std::ostringstream os;
for (size_t index = 0; index < time_sec_per_op.size(); index++) {
- os << time_sec_per_op[index] << ",";
+ double time = time_sec_per_op[index];
+ // To have good behavior when calculating total time, etc.
+ if (isnan(time)) {
+
