sethjuarez / deeplearningwithtensorflow Goto Github PK
View Code? Open in Web Editor NEWLicense: MIT License
License: MIT License
Hi Seth,
I'm trying to setup your demo (as seen on Techorama) but am running into an issue I'm not able to figure out:
When I try to run the squares.ipynb it fails in the 3rd block:
The actual error message:
ValueError Traceback (most recent call last)
<ipython-input-3-fd2d05abe21c> in <module>
4 def convert(x, y): return tf.dtypes.cast(x, tf.float32)/255., tf.one_hot(y, depth=3)
5
----> 6 train_ds = tf.data.Dataset.from_tensor_slices(generate(60000))
7 train_ds = train_ds.map(convert)
8 train_ds = train_ds.shuffle(buffer_size=1000)
C:\ProgramData\Miniconda3\envs\tf2\lib\site-packages\tensorflow_core\python\data\ops\dataset_ops.py in from_tensor_slices(tensors)
433 Dataset: A `Dataset`.
434 """
--> 435 return TensorSliceDataset(tensors)
436
437 class _GeneratorState(object):
C:\ProgramData\Miniconda3\envs\tf2\lib\site-packages\tensorflow_core\python\data\ops\dataset_ops.py in __init__(self, element)
2352 def __init__(self, element):
2353 """See `Dataset.from_tensor_slices()` for details."""
-> 2354 element = structure.normalize_element(element)
2355 batched_spec = structure.type_spec_from_value(element)
2356 self._tensors = structure.to_batched_tensor_list(batched_spec, element)
C:\ProgramData\Miniconda3\envs\tf2\lib\site-packages\tensorflow_core\python\data\util\structure.py in normalize_element(element)
109 else:
110 normalized_components.append(
--> 111 ops.convert_to_tensor(t, name="component_%d" % i))
112 return nest.pack_sequence_as(element, normalized_components)
113
C:\ProgramData\Miniconda3\envs\tf2\lib\site-packages\tensorflow_core\python\framework\ops.py in convert_to_tensor(value, dtype, name, preferred_dtype, dtype_hint)
1182 preferred_dtype = deprecation.deprecated_argument_lookup(
1183 "dtype_hint", dtype_hint, "preferred_dtype", preferred_dtype)
-> 1184 return convert_to_tensor_v2(value, dtype, preferred_dtype, name)
1185
1186
C:\ProgramData\Miniconda3\envs\tf2\lib\site-packages\tensorflow_core\python\framework\ops.py in convert_to_tensor_v2(value, dtype, dtype_hint, name)
1240 name=name,
1241 preferred_dtype=dtype_hint,
-> 1242 as_ref=False)
1243
1244
C:\ProgramData\Miniconda3\envs\tf2\lib\site-packages\tensorflow_core\python\framework\ops.py in internal_convert_to_tensor(value, dtype, name, as_ref, preferred_dtype, ctx, accept_composite_tensors)
1294
1295 if ret is None:
-> 1296 ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
1297
1298 if ret is NotImplemented:
C:\ProgramData\Miniconda3\envs\tf2\lib\site-packages\tensorflow_core\python\framework\tensor_conversion_registry.py in _default_conversion_function(***failed resolving arguments***)
50 def _default_conversion_function(value, dtype, name, as_ref):
51 del as_ref # Unused.
---> 52 return constant_op.constant(value, dtype, name=name)
53
54
C:\ProgramData\Miniconda3\envs\tf2\lib\site-packages\tensorflow_core\python\framework\constant_op.py in constant(value, dtype, shape, name)
225 """
226 return _constant_impl(value, dtype, shape, name, verify_shape=False,
--> 227 allow_broadcast=True)
228
229
C:\ProgramData\Miniconda3\envs\tf2\lib\site-packages\tensorflow_core\python\framework\constant_op.py in _constant_impl(value, dtype, shape, name, verify_shape, allow_broadcast)
233 ctx = context.context()
234 if ctx.executing_eagerly():
--> 235 t = convert_to_eager_tensor(value, ctx, dtype)
236 if shape is None:
237 return t
C:\ProgramData\Miniconda3\envs\tf2\lib\site-packages\tensorflow_core\python\framework\constant_op.py in convert_to_eager_tensor(value, ctx, dtype)
94 dtype = dtypes.as_dtype(dtype).as_datatype_enum
95 ctx.ensure_initialized()
---> 96 return ops.EagerTensor(value, ctx.device_name, dtype)
97
98
ValueError: Attempt to convert a value (220) with an unsupported type (<class 'numpy.int32'>) to a Tensor.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.