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I am trying to use a model with dynamic axis to adapt to different size of input, like [1, 3, 255,255] or [1,3,127,127]. So I have to use executeAsync to get model inference, since there is error using 'predict' method: nano_tracker.js:36 Preheat failed: Error: This execution contains the node 'StatefulPartitionedCall/assert_equal_5/Assert/AssertGuard/branch_executed/_114', which has the dynamic op 'Merge'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [Identity] at e.compile (index.js:17) at e.execute (index.js:17) at e.execute (index.js:17) at e.predict (index.js:17) at ModelBuilder._callee3$ (model_builder.js:54) at s (regeneratorRuntime.js:1) at Generator.<anonymous> (regeneratorRuntime.js:1) at Generator.next (regeneratorRuntime.js:1) at asyncGeneratorStep (asyncToGenerator.js:1) at c (asyncToGenerator.js:1)(env: Windows,mp,1.06.2405020; lib: 3.5.3)
Using executeAsync seems to get correct model inference, while memory increasing with every invoke until it fails.
Is there anyone knows how to fix this? Thank you so much
The text was updated successfully, but these errors were encountered:
"dependencies": {
"@tensorflow/tfjs-backend-cpu": "^3.5.0",
"@tensorflow/tfjs-backend-webgl": "^3.5.0",
"@tensorflow/tfjs-converter": "^3.5.0",
"@tensorflow/tfjs-core": "^3.5.0",
"fetch-wechat": "^0.0.3",
"regenerator-runtime": "^0.14.1"
},
"plugins": {
"tfjsPlugin": {
"version": "0.2.0",
"provider": "wx6afed118d9e81df9"
}
},
WeChat version: 8.0.50
WeChat base API version: 3.5.0
WeChat IDE version: 1.06.2405020 win32-x64
I am trying to use a model with dynamic axis to adapt to different size of input, like [1, 3, 255,255] or [1,3,127,127]. So I have to use executeAsync to get model inference, since there is error using 'predict' method:
nano_tracker.js:36 Preheat failed: Error: This execution contains the node 'StatefulPartitionedCall/assert_equal_5/Assert/AssertGuard/branch_executed/_114', which has the dynamic op 'Merge'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [Identity] at e.compile (index.js:17) at e.execute (index.js:17) at e.execute (index.js:17) at e.predict (index.js:17) at ModelBuilder._callee3$ (model_builder.js:54) at s (regeneratorRuntime.js:1) at Generator.<anonymous> (regeneratorRuntime.js:1) at Generator.next (regeneratorRuntime.js:1) at asyncGeneratorStep (asyncToGenerator.js:1) at c (asyncToGenerator.js:1)(env: Windows,mp,1.06.2405020; lib: 3.5.3)
Using executeAsync seems to get correct model inference, while memory increasing with every invoke until it fails.
Is there anyone knows how to fix this? Thank you so much
The text was updated successfully, but these errors were encountered: