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releasenotes/notes/33536.yaml
apiVersion: release-notes/v2 kind: bug-fix area: traffic-management issue: - 33536 releaseNotes: - |
Registered: Fri Jun 14 15:00:06 UTC 2024 - Last Modified: Mon Jun 28 17:24:43 UTC 2021 - 199 bytes - Viewed (0) -
docs_src/extra_models/tutorial005_py39.py
from fastapi import FastAPI app = FastAPI() @app.get("/keyword-weights/", response_model=dict[str, float]) async def read_keyword_weights():
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Fri Jan 07 14:11:31 UTC 2022 - 180 bytes - Viewed (0) -
src/go/doc/testdata/examples/issue43658.go
g, err := community.NewUndirectedLayers(friends, enemies) if err != nil { log.Fatal(err) } weights := []float64{1, -1} // Get the profile of internal node weight for resolutions // between 0.1 and 10 using logarithmic bisection. p, err := community.Profile( community.ModularMultiplexScore(g, weights, true, community.WeightMultiplex, 10, src), true, 1e-3, 0.1, 10, ) if err != nil { log.Fatal(err)
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Tue May 10 23:13:45 UTC 2022 - 6.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/end2end/fake_quant_per_channel.pbtxt
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 18.1K bytes - Viewed (0) -
releasenotes/notes/28942.yaml
apiVersion: release-notes/v2 kind: bug-fix area: networking issue: - 28970 releaseNotes: - |
Registered: Fri Jun 14 15:00:06 UTC 2024 - Last Modified: Thu Dec 03 16:45:33 UTC 2020 - 185 bytes - Viewed (0) -
docs_src/extra_models/tutorial005.py
from typing import Dict from fastapi import FastAPI app = FastAPI() @app.get("/keyword-weights/", response_model=Dict[str, float]) async def read_keyword_weights():
Registered: Mon Jun 17 08:32:26 UTC 2024 - Last Modified: Thu Mar 26 19:09:53 UTC 2020 - 205 bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/passes.td
let description = [{ This pass encodes sparse weights in the model in the proper format, and adds Densify() op if necessary. The general algorithm is: 1. Get list of operands (weights) of an op that can be sparse. 2. Get list of supported block configurations of the op. 3. Calculate random sparsity of the weight. 3.1. If sparsity level is below the encoding threshold, keep in dense.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 24 20:30:06 UTC 2024 - 22.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/end2end/fake_quant_per_channel_4bit.pbtxt
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 18.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/debuginfo/v1_1.0_224_frozen.wrong_attr.line.part.pbtxt
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jul 27 18:59:05 UTC 2023 - 16.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_driver.h
const bool disable_per_channel_; // We should distinguish weights and bias constants. Biases are specified by // the quantization spec or are the operands of ops with same scale spec. The // rest are weights. DenseSet<Operation*> weights_; // The weights require narrow_range quantization. This map collects all the // weight operands defined by the op quant spec. The value of each entry is
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Mar 20 11:42:17 UTC 2024 - 16.8K bytes - Viewed (0)