ValueError: Input 0 of layer dense is incompatible with the layer: : expected min_ndim=2, found ndim=1. Full shape received: [None]Keras AttributeError: 'list' object has no attribute 'ndim'LSTM with Keras: Input 'ref' of 'Assign' Op requires l-value inputError while doing reshapeRunning Tensorflow undefined symbol: PyClass_TypeError executing rnn model . How to fix it?Why am I getting Keras shape mismatch?Keras batch_size problem when using model.fit in custom layersAttributeError: 'Sequential' object has no attribute 'total_loss''Tensor' object has no attribute 'ndim'
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ValueError: Input 0 of layer dense is incompatible with the layer: : expected min_ndim=2, found ndim=1. Full shape received: [None]
Keras AttributeError: 'list' object has no attribute 'ndim'LSTM with Keras: Input 'ref' of 'Assign' Op requires l-value inputError while doing reshapeRunning Tensorflow undefined symbol: PyClass_TypeError executing rnn model . How to fix it?Why am I getting Keras shape mismatch?Keras batch_size problem when using model.fit in custom layersAttributeError: 'Sequential' object has no attribute 'total_loss''Tensor' object has no attribute 'ndim'
.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty margin-bottom:0;
1
I am new to Tensorflow and trying to work on it using the sample code below:
def build_model():
model = keras.Sequential([
layers.Dense(10, activation=tf.nn.relu),
layers.Dense(10, activation=tf.nn.relu),
layers.Dense(1)
])
optimizer = tf.keras.optimizers.RMSprop(0.001)
model.compile(loss='mean_squared_error',
optimizer=optimizer,
metrics=['mean_absolute_error', 'mean_squared_error'])
return model
model = build_model()
model.fit(training_dataset, epochs=5, steps_per_epoch=179)
The training_dataset is as below with 179 rows:
features:[29225 29259 29210 29220] Label:2
features:[29220 29236 29201 29234] Label:1
features:[29234 29241 29211 29221] Label:2
features:[29221 29224 29185 29185] Label:2
features:[29185 29199 29181 29191] Label:2
features:[29191 29195 29171 29195] Label:1
features:[29195 29228 29189 29225] Label:1
features:[29225 29236 29196 29199] Label:2
features:[29199 29222 29197 29218] Label:1
features:[29218 29235 29207 29224] Label:1
features:[29224 29244 29223 29234] Label:1
features:[29234 29247 29222 29240] Label:1
features:[29240 29264 29240 29263] Label:1
features:[29263 29267 29234 29237] Label:1
features:[29237 29270 29232 29267] Label:0
features:[29267 29270 29252 29253] Label:2
And I got the following error when running it:
"ValueError: Input 0 of layer dense is incompatible with the layer: : expected min_ndim=2, found ndim=1. Full shape received: [None]".
Can anyone advise on how to fix it?
Traceback (most recent call last):
File "ML.py", line 145, in <module>
model.fit(training_dataset, epochs=5, steps_per_epoch=179)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 851, in fit
initial_epoch=initial_epoch)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training_generator.py", line 191, in model_iteration
batch_outs = batch_function(*batch_data)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 1175, in train_on_batch
x, y, sample_weight=sample_weight, class_weight=class_weight)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 2289, in _standardize_user_data
self._set_inputs(cast_inputs)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/training/checkpointable/base.py", line 442, in _method_wrapper
method(self, *args, **kwargs)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 2529, in _set_inputs
outputs = self.call(inputs, training=training)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/sequential.py", line 233, in call
inputs, training=training, mask=mask)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/sequential.py", line 254, in _call_and_compute_mask
layer._maybe_build(x)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py", line 1591, in _maybe_build
self.input_spec, inputs, self.name)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/input_spec.py", line 139, in assert_input_compatibility
str(x.shape.as_list()))
ValueError: Input 0 of layer dense is incompatible with the layer: : expected min_ndim=2, found ndim=1. Full shape received: [None]
python tensorflow
edited Mar 28 at 4:27
jkdev
5,8836 gold badges39 silver badges69 bronze badges
asked Mar 28 at 3:54
LoKLoK
194 bronze badges
add a comment |
1
I am new to Tensorflow and trying to work on it using the sample code below:
def build_model():
model = keras.Sequential([
layers.Dense(10, activation=tf.nn.relu),
layers.Dense(10, activation=tf.nn.relu),
layers.Dense(1)
])
optimizer = tf.keras.optimizers.RMSprop(0.001)
model.compile(loss='mean_squared_error',
optimizer=optimizer,
metrics=['mean_absolute_error', 'mean_squared_error'])
return model
model = build_model()
model.fit(training_dataset, epochs=5, steps_per_epoch=179)
The training_dataset is as below with 179 rows:
features:[29225 29259 29210 29220] Label:2
features:[29220 29236 29201 29234] Label:1
features:[29234 29241 29211 29221] Label:2
features:[29221 29224 29185 29185] Label:2
features:[29185 29199 29181 29191] Label:2
features:[29191 29195 29171 29195] Label:1
features:[29195 29228 29189 29225] Label:1
features:[29225 29236 29196 29199] Label:2
features:[29199 29222 29197 29218] Label:1
features:[29218 29235 29207 29224] Label:1
features:[29224 29244 29223 29234] Label:1
features:[29234 29247 29222 29240] Label:1
features:[29240 29264 29240 29263] Label:1
features:[29263 29267 29234 29237] Label:1
features:[29237 29270 29232 29267] Label:0
features:[29267 29270 29252 29253] Label:2
And I got the following error when running it:
"ValueError: Input 0 of layer dense is incompatible with the layer: : expected min_ndim=2, found ndim=1. Full shape received: [None]".
Can anyone advise on how to fix it?
Traceback (most recent call last):
File "ML.py", line 145, in <module>
model.fit(training_dataset, epochs=5, steps_per_epoch=179)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 851, in fit
initial_epoch=initial_epoch)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training_generator.py", line 191, in model_iteration
batch_outs = batch_function(*batch_data)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 1175, in train_on_batch
x, y, sample_weight=sample_weight, class_weight=class_weight)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 2289, in _standardize_user_data
self._set_inputs(cast_inputs)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/training/checkpointable/base.py", line 442, in _method_wrapper
method(self, *args, **kwargs)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 2529, in _set_inputs
outputs = self.call(inputs, training=training)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/sequential.py", line 233, in call
inputs, training=training, mask=mask)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/sequential.py", line 254, in _call_and_compute_mask
layer._maybe_build(x)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py", line 1591, in _maybe_build
self.input_spec, inputs, self.name)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/input_spec.py", line 139, in assert_input_compatibility
str(x.shape.as_list()))
ValueError: Input 0 of layer dense is incompatible with the layer: : expected min_ndim=2, found ndim=1. Full shape received: [None]
python tensorflow
edited Mar 28 at 4:27
jkdev
5,8836 gold badges39 silver badges69 bronze badges
asked Mar 28 at 3:54
LoKLoK
194 bronze badges
add a comment |
1
1
1
2
I am new to Tensorflow and trying to work on it using the sample code below:
def build_model():
model = keras.Sequential([
layers.Dense(10, activation=tf.nn.relu),
layers.Dense(10, activation=tf.nn.relu),
layers.Dense(1)
])
optimizer = tf.keras.optimizers.RMSprop(0.001)
model.compile(loss='mean_squared_error',
optimizer=optimizer,
metrics=['mean_absolute_error', 'mean_squared_error'])
return model
model = build_model()
model.fit(training_dataset, epochs=5, steps_per_epoch=179)
The training_dataset is as below with 179 rows:
features:[29225 29259 29210 29220] Label:2
features:[29220 29236 29201 29234] Label:1
features:[29234 29241 29211 29221] Label:2
features:[29221 29224 29185 29185] Label:2
features:[29185 29199 29181 29191] Label:2
features:[29191 29195 29171 29195] Label:1
features:[29195 29228 29189 29225] Label:1
features:[29225 29236 29196 29199] Label:2
features:[29199 29222 29197 29218] Label:1
features:[29218 29235 29207 29224] Label:1
features:[29224 29244 29223 29234] Label:1
features:[29234 29247 29222 29240] Label:1
features:[29240 29264 29240 29263] Label:1
features:[29263 29267 29234 29237] Label:1
features:[29237 29270 29232 29267] Label:0
features:[29267 29270 29252 29253] Label:2
And I got the following error when running it:
"ValueError: Input 0 of layer dense is incompatible with the layer: : expected min_ndim=2, found ndim=1. Full shape received: [None]".
Can anyone advise on how to fix it?
Traceback (most recent call last):
File "ML.py", line 145, in <module>
model.fit(training_dataset, epochs=5, steps_per_epoch=179)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 851, in fit
initial_epoch=initial_epoch)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training_generator.py", line 191, in model_iteration
batch_outs = batch_function(*batch_data)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 1175, in train_on_batch
x, y, sample_weight=sample_weight, class_weight=class_weight)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 2289, in _standardize_user_data
self._set_inputs(cast_inputs)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/training/checkpointable/base.py", line 442, in _method_wrapper
method(self, *args, **kwargs)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 2529, in _set_inputs
outputs = self.call(inputs, training=training)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/sequential.py", line 233, in call
inputs, training=training, mask=mask)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/sequential.py", line 254, in _call_and_compute_mask
layer._maybe_build(x)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py", line 1591, in _maybe_build
self.input_spec, inputs, self.name)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/input_spec.py", line 139, in assert_input_compatibility
str(x.shape.as_list()))
ValueError: Input 0 of layer dense is incompatible with the layer: : expected min_ndim=2, found ndim=1. Full shape received: [None]
python tensorflow
edited Mar 28 at 4:27
jkdev
5,8836 gold badges39 silver badges69 bronze badges
asked Mar 28 at 3:54
LoKLoK
194 bronze badges
I am new to Tensorflow and trying to work on it using the sample code below:
def build_model():
model = keras.Sequential([
layers.Dense(10, activation=tf.nn.relu),
layers.Dense(10, activation=tf.nn.relu),
layers.Dense(1)
])
optimizer = tf.keras.optimizers.RMSprop(0.001)
model.compile(loss='mean_squared_error',
optimizer=optimizer,
metrics=['mean_absolute_error', 'mean_squared_error'])
return model
model = build_model()
model.fit(training_dataset, epochs=5, steps_per_epoch=179)
The training_dataset is as below with 179 rows:
features:[29225 29259 29210 29220] Label:2
features:[29220 29236 29201 29234] Label:1
features:[29234 29241 29211 29221] Label:2
features:[29221 29224 29185 29185] Label:2
features:[29185 29199 29181 29191] Label:2
features:[29191 29195 29171 29195] Label:1
features:[29195 29228 29189 29225] Label:1
features:[29225 29236 29196 29199] Label:2
features:[29199 29222 29197 29218] Label:1
features:[29218 29235 29207 29224] Label:1
features:[29224 29244 29223 29234] Label:1
features:[29234 29247 29222 29240] Label:1
features:[29240 29264 29240 29263] Label:1
features:[29263 29267 29234 29237] Label:1
features:[29237 29270 29232 29267] Label:0
features:[29267 29270 29252 29253] Label:2
And I got the following error when running it:
"ValueError: Input 0 of layer dense is incompatible with the layer: : expected min_ndim=2, found ndim=1. Full shape received: [None]".
Can anyone advise on how to fix it?
Traceback (most recent call last):
File "ML.py", line 145, in <module>
model.fit(training_dataset, epochs=5, steps_per_epoch=179)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 851, in fit
initial_epoch=initial_epoch)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training_generator.py", line 191, in model_iteration
batch_outs = batch_function(*batch_data)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 1175, in train_on_batch
x, y, sample_weight=sample_weight, class_weight=class_weight)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 2289, in _standardize_user_data
self._set_inputs(cast_inputs)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/training/checkpointable/base.py", line 442, in _method_wrapper
method(self, *args, **kwargs)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py", line 2529, in _set_inputs
outputs = self.call(inputs, training=training)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/sequential.py", line 233, in call
inputs, training=training, mask=mask)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/sequential.py", line 254, in _call_and_compute_mask
layer._maybe_build(x)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/base_layer.py", line 1591, in _maybe_build
self.input_spec, inputs, self.name)
File "/home/sandbox/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/input_spec.py", line 139, in assert_input_compatibility
str(x.shape.as_list()))
ValueError: Input 0 of layer dense is incompatible with the layer: : expected min_ndim=2, found ndim=1. Full shape received: [None]
python tensorflow
python tensorflow
edited Mar 28 at 4:27
jkdev
5,8836 gold badges39 silver badges69 bronze badges
asked Mar 28 at 3:54
LoKLoK
194 bronze badges
edited Mar 28 at 4:27
jkdev
5,8836 gold badges39 silver badges69 bronze badges
asked Mar 28 at 3:54
LoKLoK
194 bronze badges
edited Mar 28 at 4:27
jkdev
5,8836 gold badges39 silver badges69 bronze badges
edited Mar 28 at 4:27
jkdev
5,8836 gold badges39 silver badges69 bronze badges
edited Mar 28 at 4:27
jkdev
5,8836 gold badges39 silver badges69 bronze badges
5,8836 gold badges39 silver badges69 bronze badges
asked Mar 28 at 3:54
LoKLoK
194 bronze badges
asked Mar 28 at 3:54
LoKLoK
194 bronze badges
asked Mar 28 at 3:54
LoKLoK
194 bronze badges
194 bronze badges
add a comment |
add a comment |
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