The quant_stock from ltnguyen14

InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'input_1' with dtype float [[Node: input_1 = Placeholder[dtype=DT_FLOAT, shape=<unknown>, _device="/job:localhost/replica:0/task:0/cpu:0"](

I have successfully ran the trainer. / when I go to backtest - it fails.
Actually on closer inspection - I can see a bug. saving doesn't recognize tensor shape.
Tensor("output:0", shape=(?, 1), dtype=float32)

which version of tensorflow are you using?

python driver.py -t feedforward

2017-10-30 15:01:45.434854: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations. 2017-10-30 15:01:45.435181: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations. 2017-10-30 15:01:45.435203: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations. 2017-10-30 15:01:45.435214: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations. Lag 0 epoch 0 loss: 59128972527.1 Lag 0 epoch 1 loss: 46587011848.4 Lag 0 epoch 2 loss: 26121063660.8 Lag 0 epoch 3 loss: 29749124009.9 Lag 0 epoch 4 loss: 14901238999.3 The best lag is: 0 Epoch 0 completed out of 5 loss: 418341134612.0 Epoch 1 completed out of 5 loss: 49366656580.6 Epoch 2 completed out of 5 loss: 25395777597.4 Epoch 3 completed out of 5 loss: 17968284636.1 Epoch 4 completed out of 5 loss: 24333348789.0 Accuracy: 0.009250693802035153 Model saved in file: data/model/feedforward.ckpt Tensor("output:0", **shape=(?,** 1), dtype=float32)

python driver.py -b feedforward
Value before transactions: 100000
Loading pre-trained model...
2017-10-30 15:15:29.298250: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2017-10-30 15:15:29.298280: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2017-10-30 15:15:29.298295: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2017-10-30 15:15:29.298299: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Model loaded...
Traceback (most recent call last):
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1327, in _do_call
    return fn(*args)
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1306, in _run_fn
    status, run_metadata)
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/contextlib.py", line 66, in __exit__
    next(self.gen)
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/framework/errors_impl.py", line 466, in raise_exception_on_not_ok_status
    pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.InvalidArgumentError: You must feed a value for placeholder tensor 'input_1' with dtype float
	 [[Node: input_1 = Placeholder[dtype=DT_FLOAT, shape=<unknown>, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "driver.py", line 8, in <module>
    main()
  File "driver.py", line 5, in main
    inputHandler(inputs)
  File "/Users/jpope/Documents/cryptoWorkspace/Quant_stock/misc/arg_handler.py", line 31, in __init__
    self.run(FeedforwardStrategy)
  File "/Users/jpope/Documents/cryptoWorkspace/Quant_stock/misc/arg_handler.py", line 35, in run
    backtest_obj.run(plot=False)
  File "/Users/jpope/Documents/cryptoWorkspace/Quant_stock/pipeline/backtest.py", line 110, in run
    self.cerebro.run()
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/backtrader/cerebro.py", line 1127, in run
    runstrat = self.runstrategies(iterstrat)
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/backtrader/cerebro.py", line 1214, in runstrategies
    strat = stratcls(*sargs, **skwargs)
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/backtrader/metabase.py", line 88, in __call__
    _obj, args, kwargs = cls.doinit(_obj, *args, **kwargs)
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/backtrader/metabase.py", line 78, in doinit
    _obj.__init__(*args, **kwargs)
  File "/Users/jpope/Documents/cryptoWorkspace/Quant_stock/pipeline/strategies/ff_strat.py", line 30, in __init__
    print(self.sess.run(prediction, feed_dict={x: [[10.0]]}))
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 895, in run
    run_metadata_ptr)
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1124, in _run
    feed_dict_tensor, options, run_metadata)
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1321, in _do_run
    options, run_metadata)
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1340, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: You must feed a value for placeholder tensor 'input_1' with dtype float
	 [[Node: input_1 = Placeholder[dtype=DT_FLOAT, shape=<unknown>, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

Caused by op 'input_1', defined at:
  File "driver.py", line 8, in <module>
    main()
  File "driver.py", line 5, in main
    inputHandler(inputs)
  File "/Users/jpope/Documents/cryptoWorkspace/Quant_stock/misc/arg_handler.py", line 31, in __init__
    self.run(FeedforwardStrategy)
  File "/Users/jpope/Documents/cryptoWorkspace/Quant_stock/misc/arg_handler.py", line 35, in run
    backtest_obj.run(plot=False)
  File "/Users/jpope/Documents/cryptoWorkspace/Quant_stock/pipeline/backtest.py", line 110, in run
    self.cerebro.run()
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/backtrader/cerebro.py", line 1127, in run
    runstrat = self.runstrategies(iterstrat)
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/backtrader/cerebro.py", line 1214, in runstrategies
    strat = stratcls(*sargs, **skwargs)
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/backtrader/metabase.py", line 88, in __call__
    _obj, args, kwargs = cls.doinit(_obj, *args, **kwargs)
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/backtrader/metabase.py", line 78, in doinit
    _obj.__init__(*args, **kwargs)
  File "/Users/jpope/Documents/cryptoWorkspace/Quant_stock/pipeline/strategies/ff_strat.py", line 23, in __init__
    self.saver = tf.train.import_meta_graph("data/model/feedforward.ckpt.meta")
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/training/saver.py", line 1698, in import_meta_graph
    **kwargs)
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/framework/meta_graph.py", line 656, in import_scoped_meta_graph
    producer_op_list=producer_op_list)
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/framework/importer.py", line 313, in import_graph_def
    op_def=op_def)
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 2630, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1204, in __init__
    self._traceback = self._graph._extract_stack()  # pylint: disable=protected-access

InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'input_1' with dtype float
	 [[Node: input_1 = Placeholder[dtype=DT_FLOAT, shape=<unknown>, _device="/job:localhost/replica:0/task:0/cpu:0"](

Strategies for each Neural Net

Hi,

Nice code, just to be sure. Did you implemented a strategy for each Neural Net? Or just for feedfoward?

class InputHandler: def __init__(self, inputs): self.inputs = inputs if self.inputs.train: self.train(self.inputs.train) if self.inputs.btest: if self.inputs.btest == "test": self.run(TestStrategy) elif self.inputs.btest == "feedfoward": self.run(FeedforwardStrategy)

Willian

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InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'input_1' with dtype float [[Node: input_1 = Placeholder[dtype=DT_FLOAT, shape=<unknown>, _device="/job:localhost/replica:0/task:0/cpu:0"](

Strategies for each Neural Net

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