cocoa-xu / tflite_beam Goto Github PK

any reason they are not precompiled presently?

tflite_elixir seems to have armv6 support..

It's rare but I found that it sometimes causes segfaults in the GitHub CI.

https://github.com/cocoa-xu/tflite_elixir/actions/runs/4405411900/jobs/7716261476

Use a TensorFlow Lite model to answer questions based on the content of a given passage.

• #56
  • Implement BasicTokenizer
  • Implement WordpieceTokenizer
  • Implement FullTokenizer
• Load the model and get results

related link: https://www.tensorflow.org/lite/examples/bert_qa/overview

This is rather a question about accessing tensor fields.

As I play with the Super Resolution example, I notice there are two ways to access shape and type of a tensor and they seem to give the same result at least in the context of the example. I am wondering if there is a case where we have to use the functions. Depending on it, we might need to explain in the doc or to consider deprecating the functions.

out_tensor.shape
# vs
TFLite.TFLiteTensor.dims(out_tensor)

out_tensor.type
# vs
type = TFLite.TFLiteTensor.type(out_tensor)

Here are a list of blank documents as of 2023-03-14

module docs

• TFLiteElixir (top-level module)
• TFLiteElixir.Ops.Builtin.BuiltinResolver
• TFLiteElixir.Coral

function docs

• TFLiteElixir.reset_variable_tensor/1
• TFLiteElixir.Coral.contains_edge_tpu_custom_op?/1
• TFLiteElixir.Coral.dequantize_tensor/2
• TFLiteElixir.Coral.edge_tpu_devices/0
• TFLiteElixir.Coral.get_edge_tpu_context/1
• TFLiteElixir.Coral.get_edge_tpu_context/2
• TFLiteElixir.Coral.make_edge_tpu_interpreter/2
• TFLiteElixir.FlatBufferModel.initialized/1
• TFLiteElixir.Interpreter.get_signature_defs/1
• TFLiteElixir.Interpreter.predict/2

When TFLiteTensor.to_nx/2 is called without Nx backend provided, a cryptic error can occur. I am wondering if there is a way to make this error less cryptic and/or to print a human friendly error message.

https://hexdocs.pm/tflite_elixir/TFLiteElixir.TFLiteTensor.html#to_nx/2

The error seems to occur when Nx.from_binary/3 is called.

https://hexdocs.pm/nx/Nx.html#from_binary/3

** (UndefinedFunctionError) function nil.from_binary/3 is undefined
    nil.from_binary(#Inspect.Error<
  got KeyError with message:

      """
      key :__struct__ not found in: nil. If you are using the dot syntax, such as map.field, make sure the left-hand side of the dot is a map
      """

  while inspecting:

      %{__struct__: Nx.Tensor, data: nil, names: [nil], shape: {100}, type: {:f, 32}}

  Stacktrace:

    (nx 0.5.1) lib/nx/tensor.ex:165: Inspect.Nx.Tensor.inspect/2
    (elixir 1.14.3) lib/inspect/algebra.ex:341: Inspect.Algebra.to_doc/2
    (elixir 1.14.3) lib/kernel.ex:2254: Kernel.inspect/2
    (elixir 1.14.3) lib/exception.ex:717: anonymous fn/2 in Exception.format_arity/1
    (elixir 1.14.3) lib/enum.ex:2468: Enum."-reduce/3-lists^foldl/2-0-"/3
    (elixir 1.14.3) lib/exception.ex:717: Exception.format_arity/1
    (elixir 1.14.3) lib/exception.ex:712: Exception.format_mfa/3
    (elixir 1.14.3) lib/exception.ex:623: Exception.format_stacktrace_entry/1

>, <<105, 9, 17, 64, 151, 171, 24, 191, 192, 69, 116, 62, 25, 75, 60, 63, 192, 10, 3, 192, 114, 80, 4, 63, 114, 80, 4, 64, 16, 4, 201, 63, 36, 209, 246, 63, 154, 234, 95, 191, 79, 52, 183, 190, 79, 52, 183, 190, 7, 189, ...>>, [])
    (tflite_elixir 0.1.5) lib/tflite_elixir/tflite_tensor.ex:124: TFLiteElixir.TFLiteTensor.to_nx/2

This error can be recreated just by removing :backend option in the examples/artistic_style_transfer.livemd notebook.

• #48
• #49
• #50

Right now we have something like

Nx.tensor([1, 2, 3])
|> Nx.to_binary()
|> then(&TFTensor.set_data!(input_tensor, &1))

the goal is to do the same thing without explicitly calling to_binary/from_binary (maybe also include some other functions).

tensor = Nx.tensor([1, 2, 3])
tf_tensor = Nx.backend_transfer(tensor, TFLite.Backend)

TFLite.run(model, tf_tensor)
#=> This will also return a tensor allocated on TFLite.Backend

tensor = Nx.tensor([1, 2, 3])
TFLite.run(model, tensor)

• ImageClassification
• ObjectDetection

Hi. I wanted to try it with coral but my livebook dies on the last cell in the tpu.livemd
I tried to run it as mix task but also getting

[1]    55100 segmentation fault (core dumped)  mix classify_image -m /tmp/mobilenet_v2_1.0_224_inat_bird_quant_edgetpu.tflit

I have the coredump but it's 175MB in size